Abstract : There are great expectations for quantum computing, and various efforts are being made to develop its hardware and software.
However, its scale is currently inferior, and the discrepancy is enormous compared to the high-performance computing (HPC) field.
Quantum annealing also still has many challenges in its application to practical problems.
Basic research on quantum computers is expected to develop further in the future.
In this minisymposium, we present research on quantum computing technology, especially the theory and practice of quantum annealing.
The implementations of quantum annealing will be covered both quantum annealers and quantum-inspired annealers.
[03620] QUBO encoding of inequality constraints in Quantum Minimum Fill-in algorithm
Format : Talk at Waseda University
Author(s) :
Tomoko Komiyama (University of Yamanashi)
Tomohiro Suzuki (University of Yamanashi)
Abstract : Expressing constraints with complex conditions in terms of inequalities in solving optimization problems is common. When solving problems with quantum annealing, inequality constraints must be transformed into an unconstrained quadratic form that does not contain inequalities. There are various methods for this transformation, which vary in the number of auxiliary variables to be added and the total number of solutions that will be optimal. We compare these transformation methods and discuss which is suitable for quantum annealing.
[02807] Approximate block diagonalization of symmetric matrices using a quantum annealing
Format : Talk at Waseda University
Author(s) :
Koshi Teramoto (The University of Electro-Communications)
Masaki Kugaya (The University of Electro-Communications)
Shuhei Kudo (The University of Electro-Communications)
Yusaku Yamamoto (The University of Electro-Communications)
Abstract : Approximate block diagonalization is an efficient preprocessing technique for accelerating the block Jacobi method to solve the symmetric eigenvalue problem.
The aim of this study is to speed up this process using quantum annealing.
To achieve this, we formulated it as a combinatorial optimization problem and expressed it in Quadratic Unconstrained Binary Optimization (QUBO) that can be dealt with by D-Wave's quantum annealing system.
Numerical experiments on small matrices using D-Wave Advantage show that optimal approximate block diagonalization that minimizes the off-diagonal norm can be obtained with high probability.
[03304] Performance evaluation of quantum-inspired machine and quantum simulator
Format : Talk at Waseda University
Author(s) :
Makoto Morishita (Nagoya University)
Takahiro Katagiri (Nagoya University)
Satoshi Ohshima (Kyusyu University)
Tetsuya Hoshino (Nagoya University)
Toru Nagai (Nagoya University)
Abstract : The purpose of this research is to construct a heterogeneous environment in which next-generation computers that quantum computers are equipped as an accelerator specialized for specific calculations (e.g., solving QUBO).
The performance of annealing-base and gate-base by benchmarks is evaluated as a preliminary result. In particular, we evaluated the performance of solving QUBO by the annealing-base such as digital annealers, and by the gate-base of quantum circuits implementing QAOA.
Hyperparameters such as coefficients of constraint terms appearing in the QUBO formula, and the number of unitary gates in QAOA, are tuned by utilizing Optuna in our experiment.
[03892] Use of digital annealer for HPC applications
Format : Talk at Waseda University
Author(s) :
Masatoshi kawai (Nagoya University)
Abstract : In some high-performance applications, combinatorial optimization problems (COPs) are solved in unique methods. However, solving these COPs with more constraint conditions and complex evaluation functions may improve the performance of the applications. In this study, we discuss the performance improvement obtained by using Digital Annealing to solve the complex COPs derived from lattice H-matrices with dynamic load balancing and the parallelized incomplete Cholesky conjugate gradient method using a multi-coloring technique.
[04414] Performance Evaluation of Ising Machines using Constraint Combinatorial Optimization Problems
Format : Talk at Waseda University
Author(s) :
Kazuhiko Komatsu (Tohoku University)
Makoto Onoda (Tohoku University)
Masahito Kumagai (Tohoku University)
Hiroaki Kobayashi (Tohoku University)
Abstract : Ising machines have been developed rapidly by various implementations. However, the characteristics of Ising machines have not been clarified yet because a unified evaluation method and commonly used benchmark program for Ising machines have not been established.
This research evaluates various Ising machines using constraint combinatorial optimization problems. Through the evaluation, the characteristics of Ising machines are clarified.
[04218] Nonnegative binary matrix factorization by continuous relaxation and reverse annealing
Format : Talk at Waseda University
Author(s) :
Renichiro Haba (Tohoku University)
Masayuki Ohzeki (Tohoku University)
Kazuyuki Tanaka (Tohoku University)
Abstract : In this talk, we introduce a reverse annealing framework with relaxation strategies for nonnegative/binary matrix factorization, a feature extraction technique. Reverse annealing is one of the quantum annealing techniques and its specific usage has not been well explored. Experimental results reveal performance comparable to exact optimization methods, indicating the potential for expanding the applicability of reverse annealing.
[03976] Kernel learning by quantum annealer
Format : Talk at Waseda University
Author(s) :
Yasushi Hasegawa (Tohoku University)
Hiroki Oshiyama (Tohoku University)
Masayuki Ohzeki (Tohoku University)
Abstract : Kernel methods are powerful in machine learning. It is known that shift-invariant kernels can be represented by Fourier transformation of a probability distribution of frequencies. Recently the method called Implicit Kernel Learning is proposed, which learns the probability distribution according to the given data by generative model.
We developed a new method that uses quantum annealing as a sampler to train Boltzmann machines for the probability distribution. We demonstrate our method by using D-Wave quantum annealer.
[03609] mpiQulacs: A Distributed Quantum Computer Simulator for A64FX-based Cluster Systems
Format : Talk at Waseda University
Author(s) :
Masafumi Yamazaki (Fujitsu LTD.)
Satoshi Imamura (Fujitsu LTD.)
Takumi Honda (Fujitsu LTD.)
Akihiko Kasagi (Fujitsu LTD.)
Akihiro Tabuchi (Fujitsu LTD.)
Hiroshi Nakao (Fujitsu LTD.)
Naoto Fukumoto (Fujitsu LTD.)
Kohta Nakashima (Fujitsu LTD.)
Abstract : Quantum computer simulators running on classical computers are essential for understanding real quantum states and developing emerging quantum applications. In particular, state-vector simulators, which store the complete state vector in memory can be used to analyze the behavior of all types of quantum applications.
Here, we briefly introduce a distributed state-vector simulator and describe its distributed implementation and optimization. Finally, we present the scaling performance of the large-scale simulation using an A64FX-based cluster system.
[04257] Examples of application of CMOS annealing
Format : Talk at Waseda University
Author(s) :
Akiko Masaki (Hitachi, Ltd.)
Kaho Takahashi (Hitachi, Ltd.)
Kazuo Ono (Hitachi, Ltd.)
Taro Aratani (National Institute of Maritime, Port and Aviation Technology)
Takahiro Majima (National Institute of Maritime, Port and Aviation Technology)
Abstract : Hitachi has developed CMOS annealing technology as a next-generation computing technology that can solve large-scale, complex optimization problems at high speed.
In this talk, we will introduce some examples of practical applications of CMOS annealing technology. In particular, we will present examples of applications that are proving effective in the field of public infrastructure, where there are large-scale problems that cannot be solved by conventional computing technologies.
[04116] Outline and present development status of CMOS annealing
Format : Talk at Waseda University
Author(s) :
Masanao Yamaoka (Hitachi, Ltd.)
Abstract : Today, optimization processing is important for various fields. The CMOS annealing technology, which is a new-paradigm computing technology inspired by quantum computers, was developed to accelerate the optimization processing for the new value creation. By utilizing semiconductor technology, CMOS annealing can achieve large-scale integration and can be easily implemented for the practical usage. In this talk, the outline of CMOS annealing will be introduced with some examples of actual applications as a present development status.
