6 papers
Augmenting Imaginary-Time Evolution with Local Geometric Information
Carlos L. Benavides-Riveros, Prachi Sharma, Fedor Å imkovic
Imaginary-time evolution (ITE) underpins a broad family of algorithms for ground-state preparation in quantum simulation and quantum many-body physics. In these methods, convergenc…
Reinforcement Learning Assisted Quantum Simulation of Many-Body Excited States and Real-Time Dynamics
Jiaji Zhang, Lipeng Chen, Carlos L. Benavides-Riveros
The computation of electronic excited states and real-time quantum dynamics of many-fermion systems is among the most promising applications of near-term quantum computing. In this…
Extracting Many-Body Quantum Resources within One-Body Reduced Density Matrix Functional Theory
Carlos L. Benavides-Riveros, Tomasz Wasak, Alessio Recati
Quantum Fisher information (QFI) is a central concept in quantum sciences used to quantify the ultimate precision limit of parameter estimation, detect quantum phase transitions, w…
Neural Network Solution of Non-Markovian Quantum State Diffusion and Operator Construction of Quantum Stochastic Process
Jiaji Zhang, Carlos L. Benavides-Riveros, Lipeng Chen
Non-Markovian quantum state diffusion provides a wavefunction-based framework for modeling open quantum systems. In this work, we introduce a novel machine learning approach based…
Simulating Quantum Many-Body States with Neural-Network Exponential Ansatz
Weillei Zeng, Jiaji Zhang, Lipeng Chen +1
Preparing quantum many-body states on classical or quantum devices is a very challenging task that requires accounting for exponentially large Hilbert spaces. Although this complex…
Neural Quantum Propagators for Driven-Dissipative Quantum Dynamics
Jiaji Zhang, Carlos L. Benavides-Riveros, Lipeng Chen
Describing the dynamics of strong-laser driven open quantum systems is a very challenging task that requires the solution of highly involved equations of motion. While machine lear…