science

Efficient DCQO Algorithm within the Impulse Regime for Portfolio Optimization

Alejandro Gomez Cadavid, Iraitz Montalban, Archismita Dalal, Enrique Solano, Narendra N. Hegade We propose a faster digital quantum algorithm for portfolio optimization using the digitized-counterdiabatic quantum optimization (DCQO) paradigm in the impulse regime, that is, where the counterdiabatic terms are dominant. Our approach notably reduces the circuit depth requirement of the algorithm and enhances the […]

Digital-analog quantum computing of fermion-boson models in superconducting circuits

Shubham Kumar, Narendra N. Hegade, Enrique Solano, Francisco Albarrán-Arriagada, Gabriel Alvarado Barrios We proposed the digital-analog encoding for fermion-boson models using superconducting circuits outperforming digital methods in terms of circuit depth which scales quadratically with the smaller dimension of the lattice, (e.g. for a 5X5 or 5X10000 lattice, the scaling remains 25) and, for 1D […]

Digitized-counterdiabatic quantum factorization

Narendra N. Hegade, Enrique Solano. This work shows how a simple adaptation of the work carried out by by B. Yan et al., arXiv:2212.12372 (2022) can be outperformed with a non-hybrid digitized-counterdiabatic by a factor of 6, factorizing 48-bit integer using trapped-ion hardware. Link

Digitized-Counterdiabatic Quantum Algorithm for Protein Folding

Pranav Chandarana, Narendra N. Hegade, Iraitz Montalban, Enrique Solano, Xi Chen. We apply our method of Hybrid Digitized Counterdiabatic Quantum Computing (hybrid DCQC) to proteins with up to 9 amino acids, using up to 17 qubits on quantum hardware. Specifically, we benchmark our quantum algorithm with Quantinuum’s trapped ions, Google’s and IBM’s superconducting circuits, obtaining […]

Digitized-Counterdiabatic Quantum Optimization

Narendra N. Hegade, Xi Chen, Enrique Solano Kipu’s battlehorse for combinatorial optimization outperforming state-of-the-art techniques to solve some of the most challenging industry problems. Link

Digitized-counterdiabatic quantum approximate optimization algorithm

Pranav Chandarana, Narendra N. Hegade, K. Paul, Francisco Albarrán-Arriaga, Enrique Solano, Adolfo del Campo, Xi Chen. QAOA being one of the most use variational techniques for combinatorial optimization, addition of counterdiabatic protocols shows enhancement from solving combinatorial optimization problems to finding the ground state of many-body quantum systems. Link

Approximating the quantum aproximate optimization algorithm with digital-analog interactions

David Headley, Thorge Müller, Ana Martin, Enrique Solano, Mikel Sanz, Frank K. Wilhelm. By embracing the analog capacity for multi-qubit interactions, we exploit the recently proposed digital-analog quantum computation paradigm, in which the versatility of programmable universal quantum computers and the error resilience of quantum simulators are combined to improve platforms for quantum computation, specially […]

Pioneering Quantum Algorithm for solving Black-Scholes Equation

J. Gonzáles-Conde, A. Rodríguez-Rozas, E. Solano, and M. Sanz, “Quantum Algorithm for Pricing Financial Derivatives” Link

General theory of digital-analog quantum computing (DAQC)

Adrian Parra-Rodriguez, Pavel Lougovski, Lucas Lamata, Enrique Solano, and Mikel Sanz, “Digital-Analog Quantum Computation”, Phys. Rev. A 101, 022305 (2020). This paper is the kick-off of the general theory on Digital-Analog Quantum Computing. Essentially, we proved there that we can be universal with DAQC, although we will use this mostly for bespoke Co-Design Quantum Computers […]

Implementing quantum Fourier transform via digital-analog methods (DAQC)

A. Martin, L. Lamata, E. Solano, and M. Sanz, “Digital-analog quantum algorithm for the quantum Fourier transform”, Phys. Rev. Research 2, 013012 (2020). A key example of the power of DAQC applied to the quantum Fourier transform algorithm, which is the basis of quantum phase estimation article, which is at the basis of Shor algorithm, […]