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Found 8 papers, 2 papers with code
Quantum compression with classically simulatable circuits
As we continue to find applications where the currently available noisy devices exhibit an advantage over their classical counterparts, the efficient use of quantum resources is highly desirable.
Impact of Subcarrier Allocation and User Mobility on the Uplink Performance of Multi-User Massive MIMO-OFDM Systems
Motivated by this, we consider a general subcarrier allocation scheme and derive expressions for the ICI power, uplink signal to interference plus noise ratio and the achievable uplink sum-rate, taking into account the ICI and the multi-user interference due to channel aging.
Noisy intermediate-scale quantum (NISQ) algorithms
We additionally provide a comprehensive overview of various benchmarking and software tools useful for programming and testing NISQ devices.
Natural Evolutionary Strategies for Variational Quantum Computation
We implement two specific approaches, the exponential and separable natural evolutionary strategies, for parameter optimization of PQCs and compare them against standard gradient descent.
A Feasible Approach for Automatically Differentiable Unitary Coupled-Cluster on Quantum Computers
We show that, within our framework, the gradient of an expectation value with respect to a parameterized n-fold fermionic excitation can be evaluated by four expectation values of similar form and size, whereas most standard approaches based on the direct application of the parameter-shift-rule come with an associated cost of O(2^(2n)) expectation values.
Quantum Physics Chemical Physics Computational Physics
Tequila: A platform for rapid development of quantum algorithms
As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in high demand for flexible and reliable ways to implement, test, and share new ideas.
Quantum Physics Chemical Physics Computational Physics
Noise robustness and experimental demonstration of a quantum generative adversarial network for continuous distributions
In this paper, we employ a hybrid architecture for quantum generative adversarial networks (QGANs) and study their robustness in the presence of noise.
Using Inherent Structures to design Lean 2-layer RBMs
Understanding the representational power of Restricted Boltzmann Machines (RBMs) with multiple layers is an ill-understood problem and is an area of active research.
