Dimension reduction in quantum sampling of stochastic processes

• URL: http://arxiv.org/abs/2404.10338v1
• Date: Tue, 16 Apr 2024 07:22:05 GMT
• Title: Dimension reduction in quantum sampling of stochastic processes
• Authors: Chengran Yang, Marta Florido-Llin`as, Mile Gu, Thomas J. Elliott,
• Abstract summary: We introduce a method of lossy quantum reduction that allows this memory to be compressed. We show that our approach can be highly effective in low distortion compression of both Markovian and strongly non-Markovian processes alike.
• Score: 0.6562256987706128
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum technologies offer a promising route to the efficient sampling and analysis of stochastic processes, with potential applications across the sciences. Such quantum advantages rely on the preparation of a quantum sample state of the stochastic process, which requires a memory system to propagate correlations between the past and future of the process. Here, we introduce a method of lossy quantum dimension reduction that allows this memory to be compressed, not just beyond classical limits, but also beyond current state-of-the-art quantum stochastic sampling approaches. We investigate the trade-off between the saving in memory resources from this compression, and the distortion it introduces. We show that our approach can be highly effective in low distortion compression of both Markovian and strongly non-Markovian processes alike. We further discuss the application of our results to quantum stochastic modelling more broadly.

Related papers

• Classical post-processing approach for quantum amplitude estimation [0.0]
  We propose an approach for quantum amplitude estimation (QAE) designed to enhance computational efficiency while minimizing the reliance on quantum resources. Our method leverages quantum computers to generate a sequence of signals, from which the quantum amplitude is inferred through classical post-processing techniques.
  arXiv  Detail & Related papers  (2025-02-08T15:51:31Z)
• Quantum Simulation for Dynamical Transition Rates in Open Quantum Systems [0.0]
  We introduce a novel and efficient quantum simulation method to compute dynamical transition rates in Markovian open quantum systems. Our new approach holds the potential to surpass the bottlenecks of current quantum chemical research.
  arXiv  Detail & Related papers  (2024-12-23T02:53:05Z)
• Amplification of quantum transfer and quantum ratchet [56.47577824219207]
  We study a model of amplification of quantum transfer and making it directed which we call the quantum ratchet model. The ratchet effect is achieved in the quantum control model with dissipation and sink, where the Hamiltonian depends on vibrations in the energy difference synchronized with transitions between energy levels. Amplitude and frequency of the oscillating vibron together with the dephasing rate are the parameters of the quantum ratchet which determine its efficiency.
  arXiv  Detail & Related papers  (2023-12-31T14:04:43Z)
• Near-Term Distributed Quantum Computation using Mean-Field Corrections and Auxiliary Qubits [77.04894470683776]
  We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production. We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
  arXiv  Detail & Related papers  (2023-09-11T18:00:00Z)
• Simulating Gaussian boson sampling quantum computers [68.8204255655161]
  We briefly review recent theoretical methods to simulate experimental Gaussian boson sampling networks. We focus mostly on methods that use phase-space representations of quantum mechanics. A brief overview of the theory of GBS, recent experiments and other types of methods are also presented.
  arXiv  Detail & Related papers  (2023-08-02T02:03:31Z)
• Anticipative measurements in hybrid quantum-classical computation [68.8204255655161]
  We present an approach where the quantum computation is supplemented by a classical result. Taking advantage of its anticipation also leads to a new type of quantum measurements, which we call anticipative. In an anticipative quantum measurement the combination of the results from classical and quantum computations happens only in the end.
  arXiv  Detail & Related papers  (2022-09-12T15:47:44Z)
• Quantum algorithms for quantum dynamics: A performance study on the spin-boson model [68.8204255655161]
  Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware. We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
  arXiv  Detail & Related papers  (2021-08-09T18:00:05Z)
• Quantum coarse-graining for extreme dimension reduction in modelling stochastic temporal dynamics [0.0]
  coarse-graining in quantum state space drastically reduces requisite memory dimension for modelling temporal dynamics. In contrast to classical coarse-graining, this compression is not based on temporal resolution, and brings memory-efficient modelling within reach of present quantum technologies.
  arXiv  Detail & Related papers  (2021-05-14T13:47:21Z)
• Enhancing quantum models of stochastic processes with error mitigation [0.0]
  We bridge the gap between theoretical quantum models and practical use with the inclusion of error mitigation methods. It is observed that error mitigation is successful in improving the resultant expectation values. While our results indicate that error mitigation work, we show that its methodology is ultimately constrained by hardware limitations in these quantum computers.
  arXiv  Detail & Related papers  (2021-05-13T17:45:34Z)
• Importance Sampling Scheme for the Stochastic Simulation of Quantum Spin Dynamics [0.0]
  We develop an importance sampling scheme for the simulation of quantum spin dynamics. An exact transformation is then carried out to preferentially sample trajectories that are close to the dominant one. We demonstrate that this approach is capable of reducing the temporal growth of fluctuations in the quantities.
  arXiv  Detail & Related papers  (2021-03-30T16:18:28Z)
• Continuous-time dynamics and error scaling of noisy highly-entangling quantum circuits [58.720142291102135]
  We simulate a noisy quantum Fourier transform processor with up to 21 qubits. We take into account microscopic dissipative processes rather than relying on digital error models. We show that depending on the dissipative mechanisms at play, the choice of input state has a strong impact on the performance of the quantum algorithm.
  arXiv  Detail & Related papers  (2021-02-08T14:55:44Z)

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.