Quantum algorithms for cooling: A simple case study

Daniel Molpeceres, Sirui Lu, J. Ignacio Cirac, Barbara Kraus Preparation of low-energy quantum many-body states has a wide range of applications in quantum information processing and condensed-matter physics. Quantum cooling algorithms offer a promising alternative to other methods based, for instance, on variational and adiabatic principles, or on dissipative state preparation. In this work, we investigate a set of cooling…

Classical feature map surrogates and metrics for quantum control landscapes

Martino Calzavara, Tommaso Calarco, Felix Motzoi We derive and analyze three feature map representations of parametrized quantum dynamics, which generalize variational quantum circuits. These are (i) a Lie-Fourier partial sum, (ii) a Taylor expansion, and (iii) a finite-dimensional sinc kernel regression representation. The Lie-Fourier representation is shown to have a dense spectrum with discrete peaks, that reflects control Hamiltonian properties,…

Gradients, parallelism, and variance of quantum estimates

Francesco Preti, Michael Schilling, József Zsolt Bernád, Tommaso Calarco, Francisco Cárdenas-López, Felix Motzoi Computation of observables and their gradients on near-term quantum hardware is a central aspect of any quantum algorithm. In this work, we first review standard approaches to the estimation of observables with and without quantum amplitude estimation for both cost functions and gradients, discuss sampling problems, and…

Real-time adaptive quantum error correction by model-free multi-agent learning

Manuel Guatto, Francesco Preti, Michael Schilling, Tommaso Calarco, Francisco Andrés Cárdenas-López, Felix Motzoi Can we build efficient Quantum Error Correction (QEC) that adapts on the fly to time-varying noise? In this work we say yes, and show how. We present a two level framework based on Reinforcement Learning (RL) that learns to correct even non-stationary errors from scratch. At the…

Fast neutral-atom transport and transfer between optical tweezers

Cristina Cicali, Martino Calzavara, Eloisa Cuestas, Tommaso Calarco, Robert Zeier, Felix Motzoi We study the optimization of the transport and transfer of neutral atoms between optical tweezers, both critical steps in the implementation of quantum computers and simulators. We analyze four experimentally relevant pulse shapes (piecewise linear, piecewise quadratic, minimum jerk, and a combination of linear and minimum jerk), and…

Block Encoding of Sparse Matrices via Coherent Permutation

Abhishek Setty Block encoding of sparse matrices underpins powerful quantum algorithms such as quantum singular value transformation, Hamiltonian simulation, and quantum linear solvers, but its efficient gate-level implementation for arbitrary sparse matrices remains a major challenge. We introduce a unified framework that overcomes the key obstacles of multi-controlled X gates overhead, amplitude reordering, and hardware connectivity, enabling efficient block encoding…

Universal Pulses for Superconducting Qudit Ladder Gates

Boxi Li, F. A. Cárdenas-López, Adrian Lupascu, Felix Motzoi Qudits, generalizations of qubits to multilevel quantum systems, offer enhanced computational efficiency by encoding more information per lattice cell, avoiding costly swap operations and providing even exponential speedup in some cases. Utilizing the d-level manifold, however, requires high-speed gate operations because of the stronger decoherence at higher levels. While analytical…

Resource-Efficient Hadamard Test Circuits for Nonlinear Dynamics on a Trapped-IonQuantum Computer

Eleftherios Mastorakis, Muhammad Umer, Milena Guevara-Bertsch, Juris Ulmanis, Felix Rohde and Dimitris G. Angelakis Resource-efficient, low-depth implementations of quantum circuits remain a promising strategy for achieving reliable and scalable computation on quantum hardware, as they reduce gate resources and limit the accumulation of noisy operations. Here, we propose a low-depth implementation of a class of Hadamard test circuits, complemented by…

Quantum-Inspired Tensor-Network Fractional-Step Method for Incompressible Flow in Curvilinear Coordinates

Nis-Luca van Hülst, Pia Siegl, Paul Over, Sergio Bengoechea, Tomohiro Hashizume, Mario Guillaume Cecile, Thomas Rung, Dieter Jaksch We introduce an algorithmic framework based on tensor networks for computing fluid flows around immersed objects in curvilinear coordinates. We show that the tensor network simulations can be carried out solely using highly compressed tensor representations of the flow fields and the…

Disentangling fermionic Gaussian states and entanglement transitions in unitary circuit games wtih matchgates

Raúl Morral-Yepes, Marc Langer, Adam Gammon-Smith, Barbara Kraus, Frank Pollmann In unitary circuit games, two competing parties, an "entangler" and a "disentangler", can induce an entanglement phase transition in a quantum many-body system. The transition occurs at a certain rate at which the disentangler acts. We analyze such games within the context of matchgate dynamics, which equivalently corresponds to evolutions…