Related Experiment Video
Updated: Jan 15, 2026
10:00
Gradient Echo Quantum Memory in Warm Atomic Vapor
Published on: November 11, 2013
13.2K
Variational quantum simulation of time-local quantum master equations via quantum jump.
Zhihao Lan1, Jie Liu2, Zhenyu Li2
1State Key Laboratory of Physical Chemistry of Solid Surfaces, Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
The Journal of Chemical Physics
|October 9, 2025
Summary
This study introduces a quantum algorithm for simulating complex open quantum systems, overcoming classical computation limits. The method is resilient to noise and accurately models quantum dynamics on current quantum processors.
Area of Science:
- Quantum Computing
- Quantum Information Science
- Computational Physics
Background:
- Open quantum systems with strong coupling and environmental memory are computationally challenging for classical methods.
- Simulating these systems is crucial for understanding complex quantum dynamics.
Purpose of the Study:
- To develop a variational quantum algorithm for solving time-local quantum master equations on noisy intermediate-scale quantum (NISQ) processors.
- To enable scalable simulations of open quantum systems in the NISQ era.
Main Methods:
- Utilized a pair-vector stochastic Schrödinger equation for unraveling time-local quantum master equations.
- Employed McLachlan's principle for deterministic evolution and singular-value decomposition for stochastic jump implementation.
- Integrated Hadamard tests for measuring jump rates and reduced density matrices, alongside no-evolution sampling for trajectories.
Main Results:
- The quantum algorithm successfully simulated the Redfield and fourth-order time-local non-Markovian master equations on classical simulators and a superconducting quantum processor.
- The protocol demonstrated resilience to realistic hardware noise.
- Key features of open quantum dynamics, including non-Markovian oscillations and strong-coupling effects, were accurately captured.
Conclusions:
- The proposed variational quantum algorithm offers a practical and scalable pathway for simulating complex open quantum systems.
- This work advances the capabilities of NISQ devices for tackling previously intractable quantum dynamics problems.
Related Concept Videos
02:45The Quantum-Mechanical Model of an Atom
56.5K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
56.5K
01:26Transmission-Line Differential Equations
961
Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from...
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from...
961
01:12Fermi Level Dynamics
649
The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
The work...
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
The work...
649
01:10Entropy Change in Reversible Processes
3.2K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.2K
01:23Equilibrium Conditions for a Particle
2.2K
When an object is in equilibrium, it is either at rest or moving with a constant velocity. There are two types of equilibrium: static and dynamic. Static equilibrium occurs when an object is at rest, while dynamic equilibrium occurs when an object is moving with a constant velocity. In both cases, there must be a balance of forces acting on the object.
To understand the concept of equilibrium, let us first consider the forces acting on an object. When different forces act on an object, they can...
To understand the concept of equilibrium, let us first consider the forces acting on an object. When different forces act on an object, they can...
2.2K
00:59Propagation of Uncertainty from Random Error
1.7K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
1.7K