Given its importance to many other areas of physics, from condensed-matter physics to thermodynamics, time-reversal symmetry has had relatively little influence on quantum information science. Here we develop a network-based picture of time-reversal theory, classifying Hamiltonians and quantum circuits as time symmetric or not in terms of the elements and geometries of their underlying networks. Many of the typical circuits of quantum information science are found to exhibit time asymmetry. Moreover, we show that time asymmetry in circuits can be controlled using local gates only and can simulate time asymmetry in Hamiltonian evolution. We experimentally implement a fundamental example in which controlled time-reversal asymmetry in a palind...
Causal asymmetry is one of the great surprises in predictive modeling: The memory required to predic...
Collapse models are modifications of quantum theory where the wave function is treated as physically...
Causal asymmetry is one of the great surprises in predictive modeling: The memory required to predic...
Given its importance to many other areas of physics, from condensed-matter physics to thermodynamics...
Wigner separated the possible types of symmetries in quantum theory into those symmetries that are u...
Quantum mechanics still provides new unexpected effects when considering the transport of energy and...
Quantum mechanics still provides new unexpected effects when considering the transport of energy and...
Unitary gates are an interesting resource for quantum communication in part because they are always ...
Unitary gates are interesting resources for quantum communication in part because they are always in...
In the presence of time-reversal symmetry, quantum interference gives strong corrections to the elec...
This paper considers the possibility that nonrelativistic quantum mechanics tells us that Nature car...
We propose an alternative notion of time reversal in open quantum systems as represented by linear q...
We study numerically the behavior of continuous-time quantum walks over networks which are topologic...
This is the second of two reports concerning the issue of time directionality in fundamental theoret...
There is a stark tension among different formulations of quantum theory in that some are fundamental...
Causal asymmetry is one of the great surprises in predictive modeling: The memory required to predic...
Collapse models are modifications of quantum theory where the wave function is treated as physically...
Causal asymmetry is one of the great surprises in predictive modeling: The memory required to predic...
Given its importance to many other areas of physics, from condensed-matter physics to thermodynamics...
Wigner separated the possible types of symmetries in quantum theory into those symmetries that are u...
Quantum mechanics still provides new unexpected effects when considering the transport of energy and...
Quantum mechanics still provides new unexpected effects when considering the transport of energy and...
Unitary gates are an interesting resource for quantum communication in part because they are always ...
Unitary gates are interesting resources for quantum communication in part because they are always in...
In the presence of time-reversal symmetry, quantum interference gives strong corrections to the elec...
This paper considers the possibility that nonrelativistic quantum mechanics tells us that Nature car...
We propose an alternative notion of time reversal in open quantum systems as represented by linear q...
We study numerically the behavior of continuous-time quantum walks over networks which are topologic...
This is the second of two reports concerning the issue of time directionality in fundamental theoret...
There is a stark tension among different formulations of quantum theory in that some are fundamental...
Causal asymmetry is one of the great surprises in predictive modeling: The memory required to predic...
Collapse models are modifications of quantum theory where the wave function is treated as physically...
Causal asymmetry is one of the great surprises in predictive modeling: The memory required to predic...