Related Experiment Video
Updated: Jan 31, 2026

17:14
Compact Quantum Dots for Single-molecule Imaging
Published on: October 9, 2012
18.7K
Almost compact moving breathers with fine-tuned discrete time quantum walks
I Vakulchyk1, M V Fistul1, Y Zolotaryuk1
1Center for Theoretical Physics of Complex Systems, Institute for Basic Science (IBS), Daejeon 34051, South Korea.
Chaos (Woodbury, N.Y.)
|January 3, 2019
Summary
We explored nonlinear discrete time quantum walks, finding localized excitations called breathers. These breathers exhibit superexponential spatial tails and can form compact bullets at high velocities.
Area of Science:
- Quantum physics
- Nonlinear dynamics
- Condensed matter theory
Background:
- Discrete time quantum walks are unitary maps on coupled two-level systems.
- Linear quantum walks with flat bands exhibit localized states and lack transport.
- Nonlinearities introduce complex dynamics not present in linear systems.
Purpose of the Study:
- Investigate excitation dynamics in a nonlinear discrete time quantum walk.
- Analyze the properties of localized states in the nonlinear regime.
- Explore the impact of nonlinearity on transport and localization.
Main Methods:
- Studied a nonlinear discrete time quantum walk model.
- Analyzed the behavior of solitary excitations.
- Investigated stationary and moving breather solutions.
- Examined spatial localization properties and velocity dependence.
Main Results:
- Identified a set of stationary and moving breathers.
- Breathers exhibit almost compact superexponential spatial tails.
- At maximum velocity, the moving breather becomes a compact bullet.
- Nonlinearity prevents resonances with plane waves due to absence of linear dispersion.
Conclusions:
- Nonlinear discrete time quantum walks support novel localized states (breathers).
- These breathers display unique localization properties, stronger than exponential.
- The system exhibits a transition to compact localized states (bullets) at high velocities.
Related Concept Videos
Discrete-time Fourier transform
1.1K
The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
One of the notable...
One of the notable...
1.1K
Quantum Numbers
50.0K
It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
50.0K
Basic Discrete Time Signals
715
The unit step sequence is defined as 1 for zero and positive values of the integer n. This sequence can be graphically displayed using a set of eight sample points, showing a step function starting from n=0 and remaining constant thereafter.
The unit impulse or sample sequence is mathematically expressed as zero for all n values except at n=0, where it is one. The unit impulse sequence, denoted by δ(n), is the first difference of the unit step sequence, while the unit step sequence u(n) is the...
The unit impulse or sample sequence is mathematically expressed as zero for all n values except at n=0, where it is one. The unit impulse sequence, denoted by δ(n), is the first difference of the unit step sequence, while the unit step sequence u(n) is the...
715
Discrete-Time Fourier Series
680
The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
For a discrete-time periodic signal x[n]...
680
BIBO stability of continuous and discrete -time systems
921
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
921
Compact Bone
16.5K
Most bones contain compact and spongy osseous tissue, but their distribution and concentration vary based on the bone's overall function.
Compact bone, also called cortical bone, is the denser, stronger of the two types of bone tissue. It is found under the periosteum and in the diaphyses of long bones, where it provides support and protection. The microscopic structural unit of compact bone is called an osteon, or haversian system. Each osteon is composed of concentric rings of calcified...
Compact bone, also called cortical bone, is the denser, stronger of the two types of bone tissue. It is found under the periosteum and in the diaphyses of long bones, where it provides support and protection. The microscopic structural unit of compact bone is called an osteon, or haversian system. Each osteon is composed of concentric rings of calcified...
16.5K

