Transfer learning from Hermitian to non-Hermitian quantum many-body physics

Abstract

Identifying phase boundaries of interacting systems is one of the key steps to understanding quantum many-body models. The development of various numerical and analytical methods has allowed exploring the phase diagrams of many Hermitian interacting systems. However, numerical challenges and scarcity of analytical solutions hinder obtaining phase boundaries in non-Hermitian many-body models. Recent machine learning methods have emerged as a potential strategy to learn phase boundaries from various observables without having access to the full many-body wavefunction. Here, we show that a machine learning methodology trained solely on Hermitian correlation functions allows identifying phase boundaries of non-Hermitian interacting models. These results demonstrate that Hermitian machine learning algorithms can be redeployed to non-Hermitian models without requiring further training to reveal non-Hermitian phase diagrams. Our findings establish transfer learning as a versatile strategy to leverage Hermitian physics to machine learning non-Hermitian phenomena.

arXiv comment4+2 pages, 4+4 figures

References in corpus (99)

• Machine learning and the physical sciences
• Solving the Quantum Many-Body Problem with Artificial Neural Networks
• A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States
• Exceptional Topology of Non-Hermitian Systems
• Non-Hermitian Physics
• Graphene bilayer with a twist: electronic structure
• Topological phases of non-Hermitian systems
• Symmetry and Topology in Non-Hermitian Physics
• Computational complexity and fundamental limitations to fermionic quantum Monte Carlo simulations
• Nematic order in iron superconductors - who is in the driver's seat?
• Fractional quantum Hall states at zero magnetic field
• A high-bias, low-variance introduction to Machine Learning for physicists
• Graphene Bilayers with a Twist
• Symmetry protection of topological order in one-dimensional quantum spin systems
• Matrix Product States and Projected Entangled Pair States: Concepts, Symmetries, and Theorems
• Learning phase transitions by confusion
• Fractional quantum Hall effect in the absence of Landau levels
• Tensor networks for complex quantum systems
• Observation of parity-time symmetry breaking transitions in a dissipative Floquet system of ultracold atoms
• Area laws in a many-body localized state and its implications for topological order
• Machine learning quantum phases of matter beyond the fermion sign problem
• The remarkable underlying ground states of cuprate superconductors
• Quantum Monte Carlo Calculations with Chiral Effective Field Theory Interactions
• Neural-Network Approach to Dissipative Quantum Many-Body Dynamics
• Identifying topological order through unsupervised machine learning
• A review of progress in the physics of open quantum systems: theory and experiment
• Theory of Non-Hermitian Fermionic Superfluidity with a Complex-Valued Interaction
• Entanglement Phase Transition Induced by the Non-Hermitian Skin Effect
• Ferromagnetic Mott State in Twisted Graphene Bilayers at the Magic Angle
• Unsupervised machine learning and band topology
• Quantum jumps in the non-Hermitian dynamics of a superconducting qubit
• Exact Liouvillian Spectrum of a One-Dimensional Dissipative Hubbard Model
• Dynamical Control of Quantum Heat Engines Using Exceptional Points
• Decoherence Induced Exceptional Points in a Dissipative Superconducting Qubit
• Discriminative Cooperative Networks for Detecting Phase Transitions
• Volume-to-Area Law Entanglement Transition in a non-Hermitian Free Fermionic Chain
• Universal properties of dissipative Tomonaga-Luttinger liquids: Case study of a non-Hermitian XXZ spin chain
• Breakdown of the Mott insulator: Exact solution of an asymmetric Hubbard model
• Neural network wave functions and the sign problem
• Quenches near Ising quantum criticality as a challenge for artificial neural networks
• Dynamical sign reversal of magnetic correlations in dissipative Hubbard models
• Optical excitations in a one-dimensional Mott insulator
• Non-Hermitian skin clusters from strong interactions
• Experimental identification of the second-order non-Hermitian skin effect with physics-graph-informed machine learning
• Topological quantum state control through exceptional-point proximity
• PT spectroscopy of the Rabi problem
• Non-Hermitian Topological Phases: Principles and Prospects
• Enhancement of quantum heat engine by encircling a Liouvillian exceptional point
• Unsupervised identification of topological order using predictive models
• Learning phase transitions from dynamics
• Transfer learning for scalability of neural-network quantum states
• Optimizing Design Choices for Neural Quantum States
• Optimizing superconductivity: from cuprates via nickelates to palladates
• Proposal for Observing Yang-Lee Criticality in Rydberg Atomic Arrays
• Interpretable Machine Learning Study of Many-Body Localization Transition in Disordered Quantum Ising Spin Chains
• Mitigating Barren Plateaus with Transfer-learning-inspired Parameter Initializations
• Machine learning topological invariants of non-Hermitian systems
• Pairing and non-Fermi liquid behavior in partially flat-band systems
• Unsupervised and supervised learning of interacting topological phases from single-particle correlation functions
• Universal description of dissipative Tomonaga-Luttinger liquids with SU($N$) spin symmetry: Exact spectrum and critical exponents
• Non-Hermitian many-body topological excitations in interacting quantum dots
• Symmetry-protected exceptional and nodal points in non-Hermitian systems
• Level statistics of real eigenvalues in non-Hermitian systems
• Fractionalization and topology in amorphous electronic solids
• Electric-field-tunable electronic nematic order in twisted double-bilayer graphene
• Relating correlation measures: the importance of the energy gap
• $\eta$-pairing ground states in the non-Hermitian Hubbard model
• Few-body nature of Kondo correlated ground states
• Correlation-Enhanced Neural Networks as Interpretable Variational Quantum States
• Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models
• Deep Learning of Quantum Many-Body Dynamics via Random Driving
• Enhanced superconducting pairing strength near a nonmagnetic nematic quantum critical point
• Mott Quantum Critical Points at finite doping
• Topological phase diagrams of exactly solvable non-Hermitian interacting Kitaev chains
• Machine learning non-Hermitian topological phases
• Complex fixed points of the non-Hermitian Kondo model in a Luttinger liquid
• Designing quantum many-body matter with conditional generative adversarial networks
• Photonic quantum simulations of coupled $PT$-symmetric Hamiltonians
• Observation of two PT transitions in an electric circuit with balanced gain and loss
• Quantum Liouvillian exceptional and diabolical points for bosonic fields with quadratic Hamiltonians: The Heisenberg-Langevin equation approach
• Quantum criticality in interacting bosonic Kitaev-Hubbard models
• Slow down of the electronic relaxation close to the Mott transition
• An Amelioration for the Sign Problem: Adiabatic Quantum Monte Carlo
• Gaussian Process States: A data-driven representation of quantum many-body physics
• Nonlinear Landauer formula: Nonlinear response theory of disordered and topological materials
• Introduction to the theory of open quantum systems
• Extracting electronic many-body correlations from local measurements with artificial neural networks
• Magnetic vortex liquid and anomalous thermal Hall conductivity in frustrated magnets with bond-dependent interactions
• Continuous Mott transition in moiré semiconductors: role of long-wavelength inhomogeneities
• Exactly solvable $\mathcal{P}\mathcal{T}$-symmetric models in two dimensions
• Nematicity-enhanced superconductivity in systems with a non-Fermi liquid behavior
• Interaction-induced Metal to Topological Insulator Transition
• Hamiltonian inference from dynamical excitations in confined quantum magnets
• Protection of all nondefective twofold degeneracies by anti-unitary symmetries in non-Hermitian systems
• Nematic Fluctuations in an Orbital Selective Superconductor Fe${}_{1+y}$Te${}_{1-x}$Se${}_x$
• Machine learning the Kondo entanglement cloud from local measurements
• Non-Hermitian topological quantum states in a reservoir-engineered transmon chain
• Non-Hermitian chiral anomalies in interacting systems
• Raising the $\mathcal{P}\mathcal{T}$ transition threshold by strong coupling to neutral chains

Cited by in corpus (5)

• Non-Hermitian Mott Skin Effect
• Entanglement Hamiltonian and effective temperature of non-Hermitian quantum spin ladders
• Topological phases of many-body non-Hermitian systems
• Non-Hermitian chiral anomalies in interacting systems
• Transfer learning of many-body electronic correlation entropy from local measurements