Quantum Computing

Research Summary for March 2023

By Dr Chris Mansell, Senior Scientific Writer on Terra Quantum

Below is a summary of some of the interesting research papers in quantum computing and communications we’ve looked at over the past month.


Title: Enhanced Classical Singular Value Transformations for Quantum Machine Learning
Organizations: Massachusetts Institute of Technology; Washington University
The singular quantum value transformation is a quantum algorithm that incorporates a suite of other quantum algorithms, including Grover’s algorithm, Quantum Fourier transform, and Hamiltonian simulation. In this work, the researchers designed a classical algorithm that improves upon earlier well-known algorithms and is only slower than quantum algorithms with polynomial overhead. Their “quantum-inspired” algorithm can quickly solve problems like regression, matrix inversion, and assignments – faced by service providers like Netflix – to provide personalized recommendations based on information about past behavior. They also introduce four theoretical tools that can be of particular interest.
Link: https://arxiv.org/abs/2303.01492

Title: Towards proven efficient quantum algorithms for large-scale machine learning models
Organization: University of Chicago; Chicago Quantum Exchange; qBraid Co.; Sequre; Argonne National Laboratory; University of California, Berkeley; Massachusetts Institute of Technology; The Free University of Berlin
Modern neural networks perform astonishingly, partly due to their large size. However, their size also makes them very resource intensive, so an important goal is to make them more efficient. One way to do this is to trim (that is, delete) some of the connections between neurons. This is done by setting the connection weight to zero, which increases the dispersion of the neural network. In this paper, it is said that a quantum algorithm to solve nonlinear dissipative ordinary differential equations can improve the training of sparse classical neural networks. The researchers backed up their claim by comparing their approach to networks with 103 million parameters.
Link: https://arxiv.org/abs/2303.03428

Title: Quantum computing reduces systemic risk in financial networks
Organization: New York University; University of Toronto
The web of financial obligations that exists between banks can lead to a cascade of bank failures, where the bankruptcy or illiquidity of one bank can cause another bank to end up in the same position. As with phase transitions that occur in physical systems and as in the recent case of Silicon Valley Bank, cascades often occur abruptly. With enough insight, regulators can minimally reset bank cross-ownership so that the transition will not occur in ordinary circumstances but only in rare circumstances. However, it is very computationally challenging to know how to do this in a realistic and effective way. The authors of this paper compare classical and quantum partitioning algorithms on synthetic and real data. Using D-wave quantum annealing, they found that the quantum approach could make the financial system more resilient to shocks.
Link: https://www.nature.com/articles/s41598-023-30710-z

Title: Utilizing Symmetry in Variational Quantum Machine Learning
Organization: Free University of Berlin; Porsche Digital GmbH; Fraunhofer Heinrich Hertz Institute; The Helmholtz Berlin Center for Materials and Energy
Embedding classical data into today’s quantum computers is a challenging task because it needs to be done in a practical, scalable, and usable way. The variation re-upload method is a popular approach and this paper investigates how it can be combined with ideas from representation theory, a very important field of mathematics that links abstract algebra (eg, group theory) with linear algebra. This paper finds that for two machine learning problems, using a symmetry-aware set of gates leads to noteworthy increases in generalization performance. Similar constructed gate sets have also been shown to provide advantages when applied to a variational quantum eigensolver.
Link: https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.4.010328

Title: Quantum computing for periodic solids in second quantization
Organization: Riverlane; Johnson Matthey Technology Center
This work is about quantum algorithms to calculate the ground state energies of electrons in crystalline solids. The researchers took the translational symmetry of this periodic material into account when they considered which base set to use to represent electron interactions. The best choice for their algorithm is the Wannier function. Because the algorithm needs to run on an error-corrected quantum computer, they carefully estimate the number of logic gates needed for specific tasks. In particular, they looked at two industrially relevant catalysts, nickel oxide and palladium oxide, whose ground states were not well described by existing theoretical methods. This is an environmentally conscious goal because increasing catalysis reduces the amount of energy required for chemical processes.
Link: https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.013200

Title: Quantum Deep Hedging
Organization: QC Warehouse; JP Morgan The Chase
This paper addresses two questions about how deep hedging practices that reduce risk for portfolios using data-driven models that take into account market frictions and trading constraints can be enhanced by quantum computing. The researchers first examined whether existing classical deep hedging frameworks could be enhanced using quantum deep learning. Then, using quantum reinforcement learning, they studied whether new quantum frameworks could be specified for deep hedging.
Link: https://arxiv.org/abs/2303.16585


Title: Quantum-classical processing and benchmarking at pulse levels
Organization: Quantum Machines Inc.
Many of today’s most researched quantum computing techniques, from quantum error correction to variational logic gates, require a very fine degree of control over the qubits. This control is mediated by pulse signals and often must be interspersed with fast classical calculations. To improve how well this can be done, benchmarking is essential. In this paper, a benchmark is proposed for the lowest level of a quantum computer, the pulse level. This has the advantage that the quality of the qubits and the precision of control operations can be investigated and optimized separately. The work uses a comprehensive pulse level language called quantum universal assembly.
Link: https://arxiv.org/abs/2303.03816

Title: Quantum causality emerges in the Cheshire Cat delayed-selection quantum experiment with neutrons
Organizations: Atomic Institute, Vienna University of Technology; Laue Langevin Institute; Hokkaido University
One of the first counterintuitive quantum phenomena one might learn is superposition. However, this is only the beginning. It is possible to send a neutron through an interferometer so that one of its properties (such as spin) follows one path and the neutron itself follows another. It is also possible to choose to include or remove the final beam splitter from the interferometer long after the particles have entered the apparatus. In the former case, the neutron is called the quantum Cheshire Cat because it is reminiscent of the cat in ‘Alice in Wonderland’ which can disappear while leaving behind a smile. The final setup is called the delayed choice experiment and it is equally odd in that the particles seem to start behaving differently depending on the choice not being made until after behavior has changed. New experiments have now shown that these two very strange phenomena can occur together.
Link: https://www.nature.com/articles/s41598-023-29970-6

Title: A noisy mid-scale quantum computer
Organizations: Southern University of Science and Technology; International Quantum Academy; China University of Science and Technology; RIKEN; University of Michigan
Noisy mid-scale quantum computers need no introduction, but because there has been so much research on them they deserve a review. Written by many specialists and referencing more than eight hundred papers, this article comprehensively discusses milestones and breakthroughs as well as incremental advances and more gradual markers of progress. Following the section on quantum algorithms, this paper looks at each of the major hardware platforms in turn, describes their unique strengths and weaknesses and states their fidelity and recent qubit counts. The review is invaluable to the quantum technology community because it is open access.
Link: https://link.springer.com/article/10.1007/s11467-022-1249-z

Title: Experimental Activation of Strong Local Passive States with Quantum Information
Organizations: University of California, Berkeley; Miller Institute for Basic Research in Science; University of Waterloo; Perimeter Institute for Theoretical Physics
About 15 years ago, Masahiro Hotta devised a scheme to teleport energy by quantum mechanics. Just like the original scheme for teleporting quantum states from one qubit to another, this scheme requires local operations and classical communication. In this peer-reviewed paper, for the first time, a quantum energy teleportation (QET) protocol has been implemented experimentally in a nuclear magnetic resonance system. (A later preprint by Kazuki Ikeda describes similar QET experiments in an IBM superconducting quantum computer.) In terms of theoretical applications, this is potentially useful for understanding black holes and from a practical perspective, QET might be used in conjunction with algorithmically cool qubit procedures.
Link: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.130.110801

March 31, 2023

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