Local disclosure of quantum memory in non-Markovian dynamics
- URL: http://arxiv.org/abs/2310.01205v2
- Date: Wed, 17 Apr 2024 14:07:12 GMT
- Title: Local disclosure of quantum memory in non-Markovian dynamics
- Authors: Charlotte Bäcker, Konstantin Beyer, Walter T. Strunz,
- Abstract summary: Non-Markovian processes may arise in physics due to memory effects of environmental degrees of freedom.
We propose a criterion to test locally for a truly quantum memory.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Non-Markovian processes may arise in physics due to memory effects of environmental degrees of freedom. For quantum non-Markovianity, it is an ongoing debate to clarify whether such memory effects have a verifiable quantum origin, or whether they might equally be modeled by a classical memory. In this contribution, we propose a criterion to test locally for a truly quantum memory. The approach is agnostic with respect to the environment, as it solely depends on the local dynamics of the system of interest. Experimental realizations are particularly easy, as only single-time measurements on the system itself have to be performed. We study memory in a variety of physically motivated examples, both for a time-discrete case, and for time-continuous dynamics. For the latter, we are able to provide an interesting class of non-Markovian master equations with classical memory that allows for a physically measurable quantum trajectory representation.
Related papers
- Theoretical framework for quantum associative memories [0.8437187555622164]
Associative memory refers to the ability to relate a memory with an input and targets the restoration of corrupted patterns.
We develop a comprehensive framework for a quantum associative memory based on open quantum system dynamics.
arXiv Detail & Related papers (2024-08-26T13:46:47Z) - Physical consequences of gauge optimization in quantum open systems evolutions [44.99833362998488]
We show that gauge transformations can be exploited, on their own, to optimize practical physical tasks.
First, we describe the inherent structure of the underlying symmetries in quantum Markovian dynamics.
We then analyze examples of optimization in quantum thermodynamics.
arXiv Detail & Related papers (2024-07-02T18:22:11Z) - Hysteresis and Self-Oscillations in an Artificial Memristive Quantum Neuron [79.16635054977068]
We study an artificial neuron circuit containing a quantum memristor in the presence of relaxation and dephasing.
We demonstrate that this physical principle enables hysteretic behavior of the current-voltage characteristics of the quantum device.
arXiv Detail & Related papers (2024-05-01T16:47:23Z) - Non-Markovian Quantum Mpemba effect [0.0]
We study the Mpemba effect, where a far-from-equilibrium state may relax faster than a state closer to equilibrium.
Our work provides new insights into the rich physics underlying accelerated relaxation in quantum systems.
arXiv Detail & Related papers (2024-02-08T15:41:02Z) - Variational quantum simulation using non-Gaussian continuous-variable
systems [39.58317527488534]
We present a continuous-variable variational quantum eigensolver compatible with state-of-the-art photonic technology.
The framework we introduce allows us to compare discrete and continuous variable systems without introducing a truncation of the Hilbert space.
arXiv Detail & Related papers (2023-10-24T15:20:07Z) - Characterising the Hierarchy of Multi-time Quantum Processes with Classical Memory [1.3749490831384266]
We study multi-time quantum processes with memory mechanisms that transmit only classical information forward in time.
We also study two related processes that could also be considered to have classical memory from a structural perspective.
arXiv Detail & Related papers (2023-07-21T21:08:08Z) - Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
We explore the applicability of quantum-data learning to practical problems in high-energy physics.
We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states.
The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
arXiv Detail & Related papers (2023-06-29T18:00:01Z) - A Quantum-Classical Model of Brain Dynamics [62.997667081978825]
Mixed Weyl symbol is used to describe brain processes at the microscopic level.
Electromagnetic fields and phonon modes involved in the processes are treated either classically or semi-classically.
Zero-point quantum effects can be incorporated into numerical simulations by controlling the temperature of each field mode.
arXiv Detail & Related papers (2023-01-17T15:16:21Z) - Hidden Quantum Memory: Is Memory There When Somebody Looks? [0.0]
In classical physics, memoryless dynamics and Markovian statistics are one and the same.
This is not true for quantum dynamics, first and foremost because quantum measurements are invasive.
We establish the existence of Markovian statistics gathered by probing a quantum process that nevertheless fundamentally require memory for their creation.
arXiv Detail & Related papers (2022-04-18T13:09:16Z) - Preserving quantum correlations and coherence with non-Markovianity [50.591267188664666]
We demonstrate the usefulness of non-Markovianity for preserving correlations and coherence in quantum systems.
For covariant qubit evolutions, we show that non-Markovianity can be used to preserve quantum coherence at all times.
arXiv Detail & Related papers (2021-06-25T11:52:51Z) - Quantify the Non-Markovian Process with Intervening Projections in a
Superconducting Processor [1.9790421227325208]
In the quantum regime, it is challenging to define or quantify the non-MarkovianMarkity because the measurement of a quantum system often interferes with it.
We simulate the open quantum dynamics in a superconducting processor, then characterize and quantify the non-Markovian process.
arXiv Detail & Related papers (2021-05-07T15:36:22Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.