Learning entanglement breakdown as a phase transition by confusion

• URL: http://arxiv.org/abs/2202.00348v1
• Date: Tue, 1 Feb 2022 11:41:18 GMT
• Title: Learning entanglement breakdown as a phase transition by confusion
• Authors: M.A. Gavreev, A.S. Mastiukova, E.O. Kiktenko, A.K. Fedorov
• Abstract summary: We develop an approach for revealing entanglement breakdown using a machine learning technique, which is known as 'learning by confusion' We show that the developed method provides correct answers for a variety of states, including entangled states with positive partial transpose (PPT) We also present a more practical version of the method, which is suitable for studying entanglement breakdown in noisy intermediate-scale quantum (NISQ) devices.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum technologies require methods for preparing and manipulating entangled multiparticle states. However, the problem of determining whether a given quantum state is entangled or separable is known to be an NP-hard problem in general, and even the task of detecting entanglement breakdown for a given class of quantum states is difficult. In this work, we develop an approach for revealing entanglement breakdown using a machine learning technique, which is known as 'learning by confusion'. We consider a family of quantum states, which is parameterized such that there is a single critical value dividing states within this family on separate and entangled. We demonstrate the 'learning by confusion' scheme allows determining the critical value. Specifically, we study the performance of the method for the two-qubit, two-qutrit, and two-ququart entangled state, where the standard entanglement measures do not work efficiently. In addition, we investigate the properties of the local depolarization and the generalized amplitude damping channel in the framework of the confusion scheme. Within our approach and setting the parameterization of special trajectories to construct W shapes, we obtain an entanglement-breakdown 'phase diagram' of a quantum channel, which indicates regions of entangled (separable) states and the entanglement-breakdown region. Then we extend the way of using the 'learning by confusion' scheme for recognizing whether an arbitrary given state is entangled or separable. We show that the developed method provides correct answers for a variety of states, including entangled states with positive partial transpose (PPT). We also present a more practical version of the method, which is suitable for studying entanglement breakdown in noisy intermediate-scale quantum (NISQ) devices. We demonstrate its performance using an available cloud-based IBM quantum processor.

Related papers

• Observation of disorder-free localization and efficient disorder averaging on a quantum processor [117.33878347943316]
  We implement an efficient procedure on a quantum processor, leveraging quantum parallelism, to efficiently sample over all disorder realizations. We observe localization without disorder in quantum many-body dynamics in one and two dimensions.
  arXiv  Detail & Related papers  (2024-10-09T05:28:14Z)
• Machine-learning certification of multipartite entanglement for noisy quantum hardware [1.204553980682492]
  Entanglement is a fundamental aspect of quantum physics, both conceptually and for its many applications. We develop a certification pipeline that feeds statistics of random local measurements into a non-linear dimensionality reduction algorithm. We verify the accuracy of its predictions on simulated test data, and apply it to states prepared on IBM quantum computing hardware.
  arXiv  Detail & Related papers  (2024-08-22T12:47:58Z)
• Equivariant Variational Quantum Eigensolver to detect Phase Transitions through Energy Level Crossings [0.0]
  We introduce an equivariant quantum circuit that preserves the total spin and the translational symmetry to accurately describe singlet and triplet excited states. We also assess the impact of noise on the variational state, showing that conventional mitigation techniques like Zero Noise Extrapolation reliably restore its physical properties.
  arXiv  Detail & Related papers  (2024-03-11T18:51:57Z)
• Manybody Interferometry of Quantum Fluids [0.19528996680336308]
  'Manybody Ramsey interferometry' combines adiabatic state preparation and Ramsey spectroscopy. This work opens new avenues for characterizing manybody states, paving the way for quantum computers to efficiently probe quantum matter.
  arXiv  Detail & Related papers  (2023-09-11T18:01:17Z)
• Quantum process tomography of continuous-variable gates using coherent states [49.299443295581064]
  We demonstrate the use of coherent-state quantum process tomography (csQPT) for a bosonic-mode superconducting circuit. We show results for this method by characterizing a logical quantum gate constructed using displacement and SNAP operations on an encoded qubit.
  arXiv  Detail & Related papers  (2023-03-02T18:08:08Z)
• Quantum Davidson Algorithm for Excited States [42.666709382892265]
  We introduce the quantum Krylov subspace (QKS) method to address both ground and excited states. By using the residues of eigenstates to expand the Krylov subspace, we formulate a compact subspace that aligns closely with the exact solutions. Using quantum simulators, we employ the novel QDavidson algorithm to delve into the excited state properties of various systems.
  arXiv  Detail & Related papers  (2022-04-22T15:03:03Z)
• Efficient Bipartite Entanglement Detection Scheme with a Quantum Adversarial Solver [89.80359585967642]
  Proposal reformulates the bipartite entanglement detection as a two-player zero-sum game completed by parameterized quantum circuits. We experimentally implement our protocol on a linear optical network and exhibit its effectiveness to accomplish the bipartite entanglement detection for 5-qubit quantum pure states and 2-qubit quantum mixed states.
  arXiv  Detail & Related papers  (2022-03-15T09:46:45Z)
• Quantum Causal Unravelling [44.356294905844834]
  We develop the first efficient method for unravelling the causal structure of the interactions in a multipartite quantum process. Our algorithms can be used to identify processes that can be characterized efficiently with the technique of quantum process tomography.
  arXiv  Detail & Related papers  (2021-09-27T16:28:06Z)
• An agnostic-Dolinar receiver for coherent states classification [2.6763498831034034]
  We consider the problem of discriminating quantum states, where the task is to distinguish two different quantum states with a complete classical knowledge about them. In the case the quantum states are represented by coherent states of light, we identify intermediate scenarios where partial prior information is available.
  arXiv  Detail & Related papers  (2021-06-22T16:35:42Z)
• Einselection from incompatible decoherence channels [62.997667081978825]
  We analyze an open quantum dynamics inspired by CQED experiments with two non-commuting Lindblad operators. We show that Fock states remain the most robust states to decoherence up to a critical coupling.
  arXiv  Detail & Related papers  (2020-01-29T14:15:19Z)
• Quantum Pure State Tomography via Variational Hybrid Quantum-Classical Method [8.028037262377458]
  We introduce a self-learning tomographic scheme based on the variational hybrid quantum-classical method. Our scheme is further experimentally tested using techniques of a 4-qubit nuclear magnetic resonance.
  arXiv  Detail & Related papers  (2020-01-16T14:07:27Z)

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.