Digitized counterdiabatic quantum optimization

We propose digitized-counterdiabatic quantum optimization (DCQO) to achieve polynomial enhancement over adiabatic quantum optimization for the general Ising spin-glass model, which includes the whole class of combinatorial optimization problems. This is accomplished via the digitization of adiabatic quantum algorithms that are catalyzed by the addition of nonstoquastic counterdiabatic terms. The latter is suitably chosen not only for escaping classical simulability, but also for speeding up the performance. Finding the ground state of a general Ising spin-glass Hamiltonian is used to illustrate that the inclusion of k-local nonstoquastic counterdiabatic terms can always outperform the traditional adiabatic quantum optimization with stoquastic Hamiltonians. In particular, we show that a polynomial enhancement in the ground-state success probability can be achieved for a finite-time evolution, even with the simplest two-local counterdiabatic terms. Furthermore, the considered digitization process within the gate-based quantum computing paradigm, provides the flexibility to introduce arbitrary nonstoquastic interactions. As an experimental test, we study the performance of the DCQO algorithm on cloud-based IBM's superconducting and Quantinuum's ion-trap quantum processors with up to 8 qubits. Along these lines, using our proposed paradigm on current noisy intermediate-scale quantum (NISQ) computers, quantum speedup may be reached to find approximate solutions for NP-complete and NP-hard optimization problems. We expect DCQO to become a fast-lane paradigm toward quantum advantage in the NISQ era.This work is partially supported from NSFC (12075145), STCSM (Grant No. 2019SHZDZX01-334 ZX04), EU FET Open Grant Quromorphic (828826) and EPIQUS (899368), QUANTEK Project No. (KK-2021/00070), the Basque Government through Grant No. IT1470-22 and Ministerio de Ciencia e Innovacion (PID2021-126273NB-I00). X.C. acknowledges the Ramon y Cajal program (RYC-2017-22482)

Entanglement of superconducting qubits via acceleration radiation

We show that simulated relativistic motion can generate entanglement between artificial atoms and protect them from spontaneous emission. We consider a pair of superconducting qubits coupled to a resonator mode, where the modulation of the coupling strength can mimic the harmonic motion of the qubits at relativistic speeds, generating acceleration radiation. We find the optimal feasible conditions for generating a stationary entangled state between the qubits when they are initially prepared in their ground state. Furthermore, we analyse the effects of motion on the probability of spontaneous emission in the standard scenarios of single-atom and two-atom superradiance, where one or two excitations are initially present. Finally, we show that relativistic motion induces sub-radiance and can generate a Zeno-like effect, preserving the excitations from radiative decay.This work was supported by a UPV/EHU PhD grant, UPV/EHU EHUA15/17, UPV/EHU UFI 11/55, Spanish MINECO/FEDER FIS2015-69983-P and FIS2015-70856-P, Basque Government grant IT986-16, CAM PRICYT Project QUITEMAD + S2013/ICE-2801, University Sorbonne Paris Cite EQDOL contract, and Fundacion General CSIC (Programa ComFuturo)

Speeding up quantum perceptron via shortcuts to adiabaticity

The quantum perceptron is a fundamental building block for quantum machine learning. This is a multidisciplinary field that incorporates abilities of quantum computing, such as state superposition and entanglement, to classical machine learning schemes. Motivated by the techniques of shortcuts to adiabaticity, we propose a speed-up quantum perceptron where a control field on the perceptron is inversely engineered leading to a rapid nonlinear response with a sigmoid activation function. This results in faster overall perceptron performance compared to quasi-adiabatic protocols, as well as in enhanced robustness against imperfections in the controls.We acknowledge financial support from Spanish Government via PGC2018-095113-B-I00 (MCIU/AEI/FEDER, UE), Basque Government via IT986-16, as well as from QMiCS (820505) and OpenSuperQ (820363) of the EU Flagship on Quantum Technologies, and the EU FET Open Grant Quromorphic (828826). J. C. acknowledges the Ramón y Cajal program (RYC2018- 025197-I) and the EUR2020-112117 Project of the Spanish MICINN, as well as support from the UPV/EHU through the Grant EHUrOPE. X. C. acknowledges NSFC (12075145), SMSTC (2019SHZDZX01-ZX04, 18010500400 and 18ZR1415500), the Program for Eastern Scholar and the Ramón y Cajal program of the Spanish MICINN (RYC-2017-22482). E. T. acknowledges support from Project PGC2018-094792-B-I00 (MCIU/AEI/FEDER,UE), CSIC Research Platform PTI-001, and CAM/FEDER Project No. S2018/TCS-4342 (QUITEMAD-CM

Enhanced Connectivity of Quantum Hardware with Digital-Analog Control

Quantum computers based on superconducting circuits are experiencing rapid development, with the aim to outperform classical computers in certain useful tasks in the near future. However, the currently available chip fabrication technologies limit the capability of gathering a large number of high-quality qubits in a single superconducting chip, a requirement for implementing quantum error correction. Furthermore, achieving high connectivity in a chip poses a formidable technological challenge. Here, we propose a hybrid digital-analog quantum algorithm that enhances the physical connectivity among qubits coupled by an arbitrary inhomogeneous nearest-neighbor Ising Hamiltonian and generates an arbitrary all-to-all Ising Hamiltonian only by employing single-qubit rotations. Additionally, we optimize the proposed algorithm in the number of analog blocks and in the time required for the simulation. These results take advantage of the natural evolution of the system by combining the flexibility of digital steps with the robustness of analog quantum computing, allowing us to improve the connectivity of the hardware and the efficiency of quantum algorithmThe authors acknowledge support from Spanish Government PGC2018-095113-B-I00 (MCIU/AEI/FEDER, UE) and Basque Government IT986-16. The authors also acknowledge support from the projects QMiCS (820505) and OpenSuperQ (820363) of the EU Flagship on Quantum Technologies, as well as from the EU FET Open project Quromorphic (828826). This material is also based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advance Scientific Computing Research (ASCR), under field work Proposal No. ERKJ33

Multiqubit and multilevel quantum reinforcement learning with quantum technologies

We propose a protocol to perform quantum reinforcement learning with quantum technologies. At variance with recent results on quantum reinforcement learning with superconducting circuits, in our current protocol coherent feedback during the learning process is not required, enabling its implementation in a wide variety of quantum systems. We consider diverse possible scenarios for an agent, an environment, and a register that connects them, involving multiqubit and multilevel systems, as well as open-system dynamics. We finally propose possible implementations of this protocol in trapped ions and superconducting circuits. The field of quantum reinforcement learning with quantum technologies will enable enhanced quantum control, as well as more efficient machine learning calculations.We acknowledge support from CEDENNA basal grant No. FB0807 and Direccion de Postgrado USACH (FAC-L), FONDECYT under grant No. 1140194 (JCR), Spanish MINECO/FEDER FIS2015-69983-P and Basque Government IT986-16 (LL and ES), and Ramon y Cajal Grant RYC-2012-11391 (LL)

Quantum Artificial Life in an IBM Quantum Computer

We present the first experimental realization of a quantum artificial life algorithm in a quantum computer. The quantum biomimetic protocol encodes tailored quantum behaviors belonging to living systems, namely, self-replication, mutation, interaction between individuals, and death, into the cloud quantum computer IBM ibmqx4. In this experiment, entanglement spreads throughout generations of individuals, where genuine quantum information features are inherited through genealogical networks. As a pioneering proof-of-principle, experimental data fits the ideal model with accuracy. Thereafter, these and other models of quantum artificial life, for which no classical device may predict its quantum supremacy evolution, can be further explored in novel generations of quantum computers. Quantum biomimetics, quantum machine learning, and quantum artificial intelligence will move forward hand in hand through more elaborate levels of quantum complexity. © 2018, The Author(s).We acknowledge support from Spanish MINECO/FEDER FIS2015-69983-P, UPV/EHU new PhD program, Basque Government Programa Posdoctoral de Perfeccionamiento de Personal Investigador Doctor, Basque Government IT986-16, and Ramón y Cajal Grant RYC-2012-11391

Superconducting circuit architecture for digital-analog quantum computing

[EN] We propose a superconducting circuit architecture suitable for digital-analog quantum computing (DAQC) based on an enhanced NISQ family of nearest-neighbor interactions. DAQC makes a smart use of digital steps (single qubit rotations) and analog blocks (parametrized multiqubit operations) to outperform digital quantum computing algorithms. Our design comprises a chain of superconducting charge qubits coupled by superconducting quantum interference devices (SQUIDs). Using magnetic flux control, we can activate/deactivate exchange interactions, double excitation/de-excitations, and others. As a paradigmatic example, we present an efficient simulation of an l x h fermion lattice (with 2 < l <= h), using only 2(2l + 1)(2) + 24 analog blocks. The proposed architecture design is feasible in current experimental setups for quantum computing with superconducting circuits, opening the door to useful quantum advantage with fewer resources.The authors acknowledge support from Spanish MCIU/AEI/FEDER (PGC2018-095113-B-I00), Basque Government IT98616, projects QMiCS (820505) and OpenSuperQ (820363) of EU Flagship on Quantum Technologies, EU FET Open Grants Quromorphic and EPIQUS, Shanghai STCSM (Grant No. 2019SHZDZX01-ZX04), Chilean Government Financiamiento Basal para Centros Cientificos y Tecnologicos de Excelencia (Grant No. AFB180001) and Proyecto AP_539SF, DICYT (USA-2055 Dicyt), Universidad de Santiago de Chile

PIERO PELLEGRINO, L'«animus communitatis» e l'«adprobatio legislatoris» nell'attuale dottrina canonistica della consuetudine antinomica, Dott. A. Giuffrè Editore, Milano, 1995, 1 vol. de VI + 341 pp. [RECENSIÓN]

We propose a method to generate nonclassical states of light in multimode microwave cavities. Our approach considers two-photon processes that take place in a system composed of N extended cavities and an ultrastrongly coupled light-matter system. Under specific resonance conditions, our method generates, in a deterministic manner, product states of uncorrelated photon pairs, Bell states, and W states in different modes on the extended cavities. Furthermore, the numerical simulations show that the generation scheme exhibits a collective effect which decreases the generation time in the same proportion as the number of extended cavity increases. Moreover, the entanglement encoded in the photonic states can be transferred towards ancillary two-level systems to generate genuine multipartite entanglement. Finally, we discuss the feasibility of our proposal in circuit quantum electrodynamics. This proposal could be of interest in the context of quantum random number generator, due to the quadratic scaling of the output state.The authors acknowledge support from CEDENNA, Financiamiento Basal para Centros Cientificos y Tecnologicos de Excelencia FB.0807, Direccion de Postgrado USACH, FONDECYT Grant No. 1150653 and No. 1140194, Spanish MINECO/FEDER FIS2015-69983-P, Basque Government IT986-16, and Ramon y Cajal Grant RYC-2012-11391. This material is also based upon work supported by the projects OpenSuperQ and QMiCS of the EU Flagship on Quantum Technologies, and by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR) quantum algorithm teams program, under field work proposal number ERKJ333

Portfolio optimization with digitized counterdiabatic quantum algorithms

We consider digitized-counterdiabatic quantum computing as an advanced paradigm to approach quantum advantage for industrial applications in the NISQ era. We apply this concept to investigate a discrete meanvariance portfolio optimization problem, showing its usefulness in a key finance application. Our analysis shows a drastic improvement in the success probabilities of the resulting digital quantum algorithm when approximate counterdiabatic techniques are introduced. Along these lines, we discuss the enhanced performance of our methods over variational quantum algorithms like QAOA and DC-QAOA.This work is supported by NSFC (Grant No. 12075145) , STCSM (Grant No. 2019SHZDZX01-ZX04) , EU FET Open Grant EPIQUS (No. 899368) , QUANTEK project (Grant No. KK-2021/00070) , the Basque Government through Grant No. IT1470-22, the project Grant No. PID2021-126273NB-I00 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe and ERDF Invest in your Future and the Ramon y Cajal program (Grant No. RYC-2017-22482) . F. A. -A. acknowledges ANID Subvencion a la Instalacion en la Academia SA77210018 ANID Proyecto Basal AFB 180001. Authors would also like to acknowledge the Azure quantum credits program for providing access to the Quantinuum H1 emulator

Quantum autoencoders via quantum adders with genetic algorithms

The quantum autoencoder is a recent paradigm in the field of quantum machine learning, which may enable an enhanced use of resources in quantum technologies. To this end, quantum neural networks with less nodes in the inner than in the outer layers were considered. Here, we propose a useful connection between quantum autoencoders and quantum adders, which approximately add two unknown quantum states supported in different quantum systems. Specifically, this link allows us to employ optimized approximate quantum adders, obtained with genetic algorithms, for the implementation of quantum autoencoders for a variety of initial states. Furthermore, we can also directly optimize the quantum autoencoders via genetic algorithms. Our approach opens a different path for the design of quantum autoencoders in controllable quantum platforms. (c) 2018 IOP Publishing Ltd.The authors acknowledge support from Spanish MINECO FIS2015-69983-P, Ramón y Cajal Grant RYC-2012-11391, UPV/EHU Postdoctoral Grant, and Basque Government Postdoctoral Grant POS_2017_1_0022 and IT986-16