Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userUniversal limitations on implementing resourceful unitary evolutions
61
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We derive a trade-off relation between the accuracy of implementing a desired unitary evolution using a restricted set of free unitaries and the size of the assisting system, in terms of the resource generating/losing capacity of the target unitary. In particular, this relation implies that, for any theory equipped with a resource measure satisfying lenient conditions, any resource changing unitary cannot be perfectly implemented by a free unitary applied to a system and an environment if the environment has finite dimensions. Our results are applicable to a wide class of resources including energy, asymmetry, coherence, entanglement, and magic, imposing ultimate limitations inherent in such important physical settings, as well as providing insights into operational restrictions in general resource theories.
rate research
Read More
In this paper, we try to construct black hole thermodynamics based on the fact that, the formation and evaporation of a black hole can be described by quantum unitary evolutions. First, we show that the Bekenstein-Hawking entropy $S_{BH}$ may not be a Boltzmann or thermal entropy. To confirm this statement, we show that the original black holes first law may not simply be treated as the first law of thermodynamics formally, due to some missing metric perturbations caused by matter. Then, by including those (quantum) metric perturbations, we show that the black hole formation and evaporation can be described in a unitary manner effectively, through a quantum channel between the exterior and interior of the event horizon. In this way, the paradoxes of information loss and firewall can be resolved effectively. Finally, we show that black hole thermodynamics can be constructed in an ordinary way, by constructing statistical mechanics.
We have proposed and demonstrated a general and scalable scheme for programmable unitary gates. Our method is based on matrix decomposition into diagonal and Fourier factors. Thus, we are able to construct arbitrary matrix operators only by diagonal matrices alternately acting on two photonic encoding bases that belong to a Fourier transform pair. Thus, the technical difficulties to implement arbitrary unitary operators are significantly reduced. As examples, two protocols for optical OAM and path domain are considered to verify our proposal and evaluate the performance. For OAM domain, unitary matrices with dimensionality up to 6*6 are achieved and discussed with the numerical simulations. For path domain, an average fidelity of 0.98 is evaluated through 80 experimental results with dimensionality of 3*3. Furthermore, our proposal is also potential to provide a quantum operation protocol for any other photonic domain, if there exists the corresponding transformed domain.
We demonstrate that it is possible to implement a quantum perceptron with a sigmoid activation function as an efficient, reversible many-body unitary operation. When inserted in a neural network, the perceptrons response is parameterized by the potential exerted by other neurons. We prove that such a quantum neural network is a universal approximator of continuous functions, with at least the same power as classical neural networks. While engineering general perceptrons is a challenging control problem --also defined in this work--, the ubiquitous sigmoid-response neuron can be implemented as a quasi-adiabatic passage with an Ising model. In this construct, the scaling of resources is favorable with respect to the total network size and is dominated by the number of layers. We expect that our sigmoid perceptron will have applications also in quantum sensing or variational estimation of many-body Hamiltonians.
Understanding the rich behavior that emerges from systems of interacting quantum particles, such as electrons in materials, nucleons in nuclei or neutron stars, the quark-gluon plasma, and superfluid liquid helium, requires investigation of systems that are clean, accessible, and have tunable parameters. Ultracold quantum gases offer tremendous promise for this application largely due to an unprecedented control over interactions. Specifically, $a$, the two-body scattering length that characterizes the interaction strength, can be tuned to any value. This offers prospects for experimental access to regimes where the behavior is not well understood because interactions are strong, atom-atom correlations are important, mean-field theory is inadequate, and equilibrium may not be reached or perhaps does not even exist. Of particular interest is the unitary gas, where $a$ is infinite, and where many aspects of the system are universal in that they depend only on the particle density and quantum statistics. While the unitary Fermi gas has been the subject of intense experimental and theoretical investigation, the degenerate unitary Bose gas has generally been deemed experimentally inaccessible because of three-body loss rates that increase dramatically with increasing $a$. Here, we investigate dynamics of a unitary Bose gas for timescales that are short compared to the loss. We find that the momentum distribution of the unitary Bose gas evolves on timescales fast compared to losses, and that both the timescale for this evolution and the limiting shape of the momentum distribution are consistent with universal scaling with density. This work demonstrates that a unitary Bose gas can be created and probed dynamically, and thus opens the door for further exploration of this novel strongly interacting quantum liquid.
Universal unitary photonic devices can apply arbitrary unitary transformations to a vector of input modes and provide a promising hardware platform for fast and energy-efficient machine learning using light. We simulate the gradient-based optimization of random unitary matrices on universal photonic devices composed of imperfect tunable interferometers. If device components are initialized uniform-randomly, the locally-interacting nature of the mesh components biases the optimization search space towards banded unitary matrices, limiting convergence to random unitary matrices. We detail a procedure for initializing the device by sampling from the distribution of random unitary matrices and show that this greatly improves convergence speed. We also explore mesh architecture improvements such as adding extra tunable beamsplitters or permuting waveguide layers to further improve the training speed and scalability of these devices.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
