Quantum and Classical Bayesian Agents

• URL: http://arxiv.org/abs/2106.09057v2
• Date: Wed, 11 May 2022 14:54:29 GMT
• Title: Quantum and Classical Bayesian Agents
• Authors: John B. DeBrota and Peter J. Love
• Abstract summary: We present a framework for treating multiple interacting quantum and classical Bayesian agents. A consistent treatment of multiple interacting users of quantum theory may allow us to properly interpret existing multi-agent protocols.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We describe a general approach to modeling rational decision-making agents who adopt either quantum or classical mechanics based on the Quantum Bayesian (QBist) approach to quantum theory. With the additional ingredient of a scheme by which the properties of one agent may influence another, we arrive at a flexible framework for treating multiple interacting quantum and classical Bayesian agents. We present simulations in several settings to illustrate our construction: quantum and classical agents receiving signals from an exogenous source, two interacting classical agents, two interacting quantum agents, and interactions between classical and quantum agents. A consistent treatment of multiple interacting users of quantum theory may allow us to properly interpret existing multi-agent protocols and could suggest new approaches in other areas such as quantum algorithm design.

Related papers

• Quantum Agents [0.3495246564946556]
  This paper explores the intersection of quantum computing and agentic AI.<n>We present conceptual and technical foundations for future quantum-agentic platforms.<n>We aim to chart a path toward scalable, intelligent, and adaptive quantum-agentic ecosystems.
  arXiv  Detail & Related papers  (2025-06-02T10:54:31Z)
• Operationally classical simulation of quantum states [41.94295877935867]
  A classical state-preparation device cannot generate superpositions and hence its emitted states must commute. We show that no such simulation exists, thereby certifying quantum coherence. Our approach is a possible avenue to understand how and to what extent quantum states defy generic models based on classical devices.
  arXiv  Detail & Related papers  (2025-02-03T15:25:03Z)
• Quantum Equilibrium Propagation for efficient training of quantum systems based on Onsager reciprocity [0.0]
  Equilibrium propagation (EP) is a procedure that has been introduced and applied to classical energy-based models which relax to an equilibrium. Here, we show a direct connection between EP and Onsager reciprocity and exploit this to derive a quantum version of EP. This can be used to optimize loss functions that depend on the expectation values of observables of an arbitrary quantum system.
  arXiv  Detail & Related papers  (2024-06-10T17:22:09Z)
• A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity [50.387179833629254]
  We introduce a collaborative classical-quantum architecture called co-TenQu. Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting. It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
  arXiv  Detail & Related papers  (2024-02-23T14:09:41Z)
• Ergodic and mixing quantum channels: From two-qubit to many-body quantum systems [1.9799527196428246]
  We study the ergodic theory of quantum channels by characterizing different levels of ergodic hierarchy from integrable to mixing. We also study interacting many-body quantum systems that include the famous Sachdev-Ye-Kitaev (SYK) model.
  arXiv  Detail & Related papers  (2023-10-04T11:30:57Z)
• Quantum Autoencoders for Learning Quantum Channel Codes [0.0]
  We develop a machine learning framework to generate quantum channel codes and evaluate their effectiveness. Applying it to various quantum channel models as proof of concept, we demonstrate strong performance in each case.
  arXiv  Detail & Related papers  (2023-07-13T08:37:21Z)
• Classical Verification of Quantum Learning [42.362388367152256]
  We develop a framework for classical verification of quantum learning. We propose a new quantum data access model that we call "mixture-of-superpositions" quantum examples. Our results demonstrate that the potential power of quantum data for learning tasks, while not unlimited, can be utilized by classical agents.
  arXiv  Detail & Related papers  (2023-06-08T00:31:27Z)
• A scalable superconducting quantum simulator with long-range connectivity based on a photonic bandgap metamaterial [0.0]
  We present a quantum simulator architecture based on a linear array of qubits locally connected to a superconducting photonic-bandgap metamaterial. The metamaterial acts both as a quantum bus mediating qubit-qubit interactions, and as a readout channel for multiplexed qubit-state measurement. We characterize the Hamiltonian of the system using a measurement-efficient protocol based on quantum many-body chaos.
  arXiv  Detail & Related papers  (2022-06-26T06:51:54Z)
• Entanglement catalysis for quantum states and noisy channels [41.94295877935867]
  We investigate properties of entanglement and its role for quantum communication. For transformations between bipartite pure states, we prove the existence of a universal catalyst. We further develop methods to estimate the number of singlets which can be established via a noisy quantum channel.
  arXiv  Detail & Related papers  (2022-02-10T18:36:25Z)
• Interactive Protocols for Classically-Verifiable Quantum Advantage [46.093185827838035]
  "Interactions" between a prover and a verifier can bridge the gap between verifiability and implementation. We demonstrate the first implementation of an interactive quantum advantage protocol, using an ion trap quantum computer.
  arXiv  Detail & Related papers  (2021-12-09T19:00:00Z)
• Information Scrambling in Computationally Complex Quantum Circuits [56.22772134614514]
  We experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor. We show that while operator spreading is captured by an efficient classical model, operator entanglement requires exponentially scaled computational resources to simulate.
  arXiv  Detail & Related papers  (2021-01-21T22:18:49Z)
• Experimental Quantum Generative Adversarial Networks for Image Generation [93.06926114985761]
  We experimentally achieve the learning and generation of real-world hand-written digit images on a superconducting quantum processor. Our work provides guidance for developing advanced quantum generative models on near-term quantum devices.
  arXiv  Detail & Related papers  (2020-10-13T06:57:17Z)
• Variational classical networks for dynamics in interacting quantum matter [0.0]
  We introduce a variational class of wavefunctions based on complex networks of classical spins akin to artificial neural networks. We show that our method can be applied to any quantum many-body system with a well-defined classical limit.
  arXiv  Detail & Related papers  (2020-07-31T14:03:37Z)
• From a quantum theory to a classical one [117.44028458220427]
  We present and discuss a formal approach for describing the quantum to classical crossover. The method was originally introduced by L. Yaffe in 1982 for tackling large-$N$ quantum field theories.
  arXiv  Detail & Related papers  (2020-04-01T09:16:38Z)

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.