mat2qubit: A lightweight pythonic package for qubit encodings of vibrational, bosonic, graph coloring, routing, scheduling, and general matrix problems

@article{Sawaya2022mat2qubitAL,
  title={mat2qubit: A lightweight pythonic package for qubit encodings of vibrational, bosonic, graph coloring, routing, scheduling, and general matrix problems},
  author={Nicolas PD Sawaya},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.09776}
}
Preparing problems for execution on quantum computers can require many compilation steps. Automated compilation software is useful not only for easier and faster problem execution, but also for facilitating the comparison between different algorithmic choices. Here we describe mat2qubit, a Python package for encoding several classes of classical and quantum problems into qubit repre-sentations. It is intended for use especially on Hamiltonians and functions defined over variables ( e.g. particles… 
[PDF] Semantic Reader
1 Citations
Methods Citations
1

One Citation

Improved resource-tunable near-term quantum algorithms for transition probabilities, with applications in physics and variational quantum linear algebra
Transition amplitudes and transition probabilities are relevant to many areas of physics simulation, including the calculation of response properties and correlation functions. These quantities are…

References

SHOWING 1-10 OF 60 REFERENCES
Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems
TLDR
This manuscript presents an intuitive method for synthesizing and analyzing discrete (i.e., integer-based) optimization problems, wherein the problem and corresponding algorithmic primitives are expressed using a discrete quantum intermediate representation (DQIR) that is encoding-independent.
On connectivity-dependent resource requirements for digital quantum simulation of d-level particles
TLDR
To study the number of SWAP gates required to Trotterize commonly used quantum operators, this work uses both analytical arguments and automatic tools that optimize the schedule in multiple stages to build on previous results by including effects of hardware connectivity.
Resource-efficient digital quantum simulation of d-level systems for photonic, vibrational, and spin-s Hamiltonians
Simulation of quantum systems is expected to be one of the most important applications of quantum computing, with much of the theoretical work so far having focused on fermionic and…
The Bravyi-Kitaev transformation for quantum computation of electronic structure.
TLDR
An alternative method of simulating fermions with qubits, first proposed by Bravyi and Kitaev, is developed that reduces the simulation cost to O(log n) qubit operations for one fermionic operation and demonstrates the superior efficiency of the Bravyi-Kitaev method for all quantum computations of electronic structure.
Space-efficient binary optimization for variational quantum computing
TLDR
This paper shows that it is possible to greatly reduce the number of qubits needed for the Travelling Salesman problem, a paradigmatic optimization task, at the cost of having deeper variational circuits, and claims that the approach can be generalized for other problems where the standard bit-encoding is highly inefficient.
XY mixers: Analytical and numerical results for the quantum alternating operator ansatz
TLDR
This paper explores strategies for enforcing hard constraints by using $XY$ Hamiltonians as mixing operators (mixers) and demonstrates that, for an integer variable admitting $\ensuremath{\kappa}$ discrete values represented through one-hot encoding, certain classes of the mixer Hamiltonian can be implemented without Trotter error in depth.
OpenQL : A Portable Quantum Programming Framework for Quantum Accelerators
TLDR
This article presents the programming interface of OpenQL, the different layers of the compiler and how it can provide portability over different qubit technologies, and shows that OpenQL allows the execution of the same high-level algorithm on two different qu Bit technologies, namely superconducting qubits and Si-Spin qubits.
quimb: A python package for quantum information and many-body calculations
The language of quantum physics is essentially linear algebra, making it easy to begin simulating using standard numerical routines. However, the amount of classical resources required to simulate a…
qTorch: The quantum tensor contraction handler
TLDR
The results in this work suggest that tensor contraction methods are superior only when simulating Max-Cut/QAOA with graphs of regularities approximately five and below, and that the stochastic contraction method outperforms the line graph based method only when the time to calculate a reasonable tree decomposition is prohibitively expensive.
Domain wall encoding of discrete variables for quantum annealing and QAOA
In this paper I propose a new method of encoding discrete variables into Ising model qubits for quantum optimisation. The new method is based on the physics of domain walls in one-dimensional Ising…
...
...