PUBLICATIONS

References and Links to Papers and Preprints

SIMULATION OF CONTINUOUS-VARIABLE QUANTUM SYSTEMS WITH TENSOR NETWORK

Ryutaro Nagai, Takao Tomono, Yuichiro Minato, October 2021

Tensor network is known as a powerful method to simulate quantum computation on a classical computer. Recently, the random quantum circuit used in the demonstration of quantum supremacy by Sycamore quantum computer have been simulated with tensor network method. Compared to the application of tensor networks to Discrete-Variable (DV) quantum computation, there are very few examples of application of tensor network to Continuous-Variable (CV) quantum computation. Therefore, we applied a tensor network structure called Matrix Product States (MPS) to CV quantum computation. Tensor network is expected to be useful for simulating Gaussian Boson Sampling (GBS), which is a promised near-term application of photonic quantum system. We outline the performance of tensor network-based simulation of CV quantum computation in GBS.

NEURAL SEQUENCE TRANSFORMATION

Sabyasachi Mukherjee, Sayan Mukherjee, Binh-Son Hua, Nobuyuki Umetani, Daniel Meister, August 2021

We consider the problem of accelerating sequences of Monte-Carlo estimates of a finite integral, which has a slow convergence rate. We achieve faster convergence with the help of sequence transformation: by changing the sequence of Monte-Carlo estimates into another sequence that converges faster. Demonstrating the difficulties of doing this analytically, we use a data-driven approach that works well for several 1D integrals as well as scenes in light transport simulation.

A GROVER SEARCH-BASED ALGORITHM FOR THE LIST COLORING PROBLEM

Sayan Mukherjee, August 2021

We propose a quantum algorithm based on Grover search to quadratically speed up exhaustive search for the list coloring problem.

TOWARDS ACCURATE DESCRIPTION OF CHEMICAL REACTION ENERGETICS BY USING VARIATIONAL QUANTUM EIGENSOLVER: A CASE STUDY OF THE C2V QUASI-REACTION PATHWAY OF BERYLLIUM INSERTION TO H2 MOLECULE

Kenji Sugisaki, Takumi Kato, Yuichiro Minato, Koji Okuwaki, Yuji Mochizuki, June 2021

We have examined the performance of variational quantum eigensolver along the quasi-reaction pathway of Be insertion to H2 molecule, in which avoided crossing occurs at the transition structure. Numerical simulations revealed that the multireference unitary coupled cluster with partially generalized singles and doubles (MR-UCCpGSD) is a powerful tool to describe the electronic structure of strongly correlated systems.

FINDING HIGH-ORDER HADAMARD MATRICES BY USING QUANTUM COMPUTERS

Andriyan Suksmono, Yuichiro Minato, September 2020

In this paper, we show that by adopting classical construction/search techniques of the H-matrix, we can develop new quantum computing methods to find higher order H-matrices

REDUCTION OF ORBITAL SPACE FOR MOLECULAR ORBITAL CALCULATIONS WITH QUANTUM COMPUTATION SIMULATOR FOR EDUCATIONS

Yuji Mochizuki, Koji Okuwaki, Takumi Kato, Yuichiro Minato, September 2019

Recently, the molecular orbital (MO) calculations with quantum computations (QCs) have attracted considerable interest. The cost of QCs highly depends on the number of qubits even on quantum simulators. The reduction of MO space can thus be a crucial issue for the practical applicability of MO-QC. Besides the frozen-core restriction for the occupied MO space, we have used the pseudo-natural orbital derived from the second-order M{\o}ller-Plesset perturbation (MP2) theory for the virtual MO space. A preliminary test on the LiH molecule (STO-3G basis) showed acceleration by a factor larger than 500 for MO-QC with the Blueqat simulator, where the required time was 72 s per solution. Simulations of MO-QC may be used as practical teaching materials in classes.

FINDING HADAMARD MATRICES BY A QUANTUM ANNEALING MACHINE

Andriyan Bayu Suksmono, Yuichiro Minato, October 2019

We propose a method to formulate the Hamiltonian for finding binary Hadamard matrices, and address its implementation limitation on existing quantum annealing machines.

SOLVING TILING PUZZLES WITH QUANTUM ANNEALING

Asa Eagle, Takumi Kato, Yuichiro Minato, April 2019

To solve tiling puzzles, such as "pentomino" or "tetromino" puzzles, we need to find the correct solutions out of numerous combinations of rotations or piece locations. Solving this kind of combinatorial optimization problem is a very difficult problem in computational science, and quantum computing is expected to play an important role in this field. In this article, we propose a method and obtained specific formulas to find solutions for tetromino tiling puzzles using a quantum annealer. In addition, we evaluated these formulas using a simulator and using actual hardware DW2000Q.