Tightening Quantum Speed Limits for Almost All States

Conventional quantum speed limits perform poorly for mixed quantum states: They are generally not tight and often significantly underestimate the fastest possible evolution speed. To remedy this, for unitary driving, we derive two quantum speed limits that outperform the traditional bounds for almost all quantum states. Moreover, our bounds are significantly simpler to compute as well as experimentally more accessible. Our bounds have a clear geometric interpretation; they arise from the evaluation of the angle between generalized Bloch vectors.Comment: Updated and revised version; 5 pages, 2 figures, 1 page appendi

A practical, unitary simulator for non-Markovian complex processes

Stochastic processes are as ubiquitous throughout the quantitative sciences as they are notorious for being difficult to simulate and predict. In this letter we propose a unitary quantum simulator for discrete-time stochastic processes which requires less internal memory than any classical analogue throughout the simulation. The simulator's internal memory requirements equal those of the best previous quantum models. However, in contrast to previous models it only requires a (small) finite-dimensional Hilbert space. Moreover, since the simulator operates unitarily throughout, it avoids any unnecessary information loss. We provide a stepwise construction for simulators for a large class of stochastic processes hence directly opening the possibility for experimental implementations with current platforms for quantum computation. The results are illustrated for an example process.Comment: 12 pages, 5 figure

Speeding up Thermalisation via Open Quantum System Variational Optimisation

Optimizing open quantum system evolution is an important step on the way to achieving quantum computing and quantum thermodynamic tasks. In this article, we approach optimisation via variational principles and derive an open quantum system variational algorithm explicitly for Lindblad evolution in Liouville space. As an example of such control over open system evolution, we control the thermalisation of a qubit attached to a thermal Lindbladian bath with a damping rate $\gamma$. Since thermalisation is an asymptotic process and the variational algorithm we consider is for fixed time, we present a way to discuss the potential speedup of thermalisation that can be expected from such variational algorithms.Comment: 10 pages, 4 figures, comments welcom

Quantacell: Powerful charging of quantum batteries

We study the problem of charging a quantum battery in finite time. We demonstrate an analytical optimal protocol for the case of a single qubit. Extending this analysis to an array of N qubits, we demonstrate that an N-fold advantage in power per qubit can be achieved when global operations are permitted. The exemplary analytic argument for this quantum advantage in the charging power is backed up by numerical analysis using optimal control techniques. It is demonstrated that the quantum advantage for power holds when, with cyclic operation in mind, initial and final states are required to be separable.Comment: 11 pages, 3 figures, comments welcom

Enhancing the charging power of quantum batteries

Can collective quantum effects make a difference in a meaningful thermodynamic operation? Focusing on energy storage and batteries, we demonstrate that quantum mechanics can lead to an enhancement in the amount of work deposited per unit time, i.e., the charging power, when $N$ batteries are charged collectively. We first derive analytic upper bounds for the collective \emph{quantum advantage} in charging power for two choices of constraints on the charging Hamiltonian. We then highlight the importance of entanglement by proving that the quantum advantage vanishes when the collective state of the batteries is restricted to be in the separable ball. Finally, we provide an upper bound to the achievable quantum advantage when the interaction order is restricted, i.e., at most $k$ batteries are interacting. Our result is a fundamental limit on the advantage offered by quantum technologies over their classical counterparts as far as energy deposition is concerned.Comment: In this new updated version Theorem 1 has been changed with Proposition 1. The paper has been published on PRL, and DOI included accordingl

Optimal stochastic modelling with unitary quantum dynamics

Identifying and extracting the past information relevant to the future behaviour of stochastic processes is a central task in the quantitative sciences. Quantum models offer a promising approach to this, allowing for accurate simulation of future trajectories whilst using less past information than any classical counterpart. Here we introduce a class of phase-enhanced quantum models, representing the most general means of causal simulation with a unitary quantum circuit. We show that the resulting constructions can display advantages over previous state-of-art methods - both in the amount of information they need to store about the past, and in the minimal memory dimension they require to store this information. Moreover, we find that these two features are generally competing factors in optimisation - leading to an ambiguity in what constitutes the optimal model - a phenomenon that does not manifest classically. Our results thus simultaneously offer new quantum advantages for stochastic simulation, and illustrate further qualitative differences in behaviour between classical and quantum notions of complexity.Comment: 9 pages, 5 figure

A Gillespie algorithm for efficient simulation of quantum jump trajectories

The jump unravelling of a quantum master equation decomposes the dynamics of an open quantum system into abrupt jumps, interspersed by periods of coherent dynamics where no jumps occur. Simulating these jump trajectories is computationally expensive, as it requires very small time steps to ensure convergence. This computational challenge is aggravated in regimes where the coherent, Hamiltonian dynamics are fast compared to the dissipative dynamics responsible for the jumps. Here, we present a quantum version of the Gillespie algorithm that bypasses this issue by directly constructing the waiting time distribution for the next jump to occur. In effect, this avoids the need for timestep discretisation altogether, instead evolving the system continuously from one jump to the next. We describe the algorithm in detail and discuss relevant limiting cases. To illustrate it we include four example applications of increasing physical complexity. These additionally serve to compare the performance of the algorithm to alternative approaches -- namely, the widely-used routines contained in the powerful Python library QuTip. We find significant gains in efficiency for our algorithm and discuss in which regimes these are most pronounced. Publicly available implementations of our code are provided in Julia and Mathematica.Comment: 13 pages, 4 figures. Comments welcom