LSI-BASED EFFICIENT EMULATION OVERCOMING ALGORITHMIC RESTRICTIONS INHERENT IN QUANTUM COMPUTERS

2003 ◽  
Vol 03 (04) ◽  
pp. C9-C17
Author(s):  
MINORU FUJISHIMA
Keyword(s):  
Periodic Function ◽  
Integrated Circuit ◽  
High Speed ◽  
Large Scale ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Quantum Computers ◽  
Np Problems

Quantum computers are believed to perform high-speed calculations, compared with conventional computers. However, the quantum computer solves NP (non-deterministic polynomial) problems at a high speed only when a periodic function can be used in the process of calculation. To overcome the restrictions stemming from the quantum algorithm, we are studying the emulation by a LSI (large scale integrated circuit). In this report, first, it is explained why a periodic function is required for the algorithm of a quantum computer. Then, it is shown that the LSI emulator can solve NP problems at a high speed without using a periodic function.

scholarly journals Asset–liability modelling in the quantum era

2021 ◽  
Vol 26 ◽  
Author(s):  
T. Berry ◽  
J. Sharpe
Keyword(s):  
Quantum Mechanics ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Capital Requirements ◽  
Quantum Computers ◽  
Investment Management ◽  
Asset Liability Management ◽  
Liability Management ◽  
Insight Into ◽  
Current Practices

Abstract This paper introduces and demonstrates the use of quantum computers for asset–liability management (ALM). A summary of historical and current practices in ALM used by actuaries is given showing how the challenges have previously been met. We give an insight into what ALM may be like in the immediate future demonstrating how quantum computers can be used for ALM. A quantum algorithm for optimising ALM calculations is presented and tested using a quantum computer. We conclude that the discovery of the strange world of quantum mechanics has the potential to create investment management efficiencies. This in turn may lead to lower capital requirements for shareholders and lower premiums and higher insured retirement incomes for policyholders.

The Dawn of Quantum Information

2020 ◽  
pp. 258-270
Author(s):  
Gershon Kurizki ◽  
Goren Gordon
Keyword(s):  
Quantum Information ◽  
Large Scale ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Single Step ◽  
Weather Forecasts ◽  
State Of Mind ◽  
Process Simulations ◽  
Superposition States ◽  
Quantum Revolution

Henry and Eve have finally tested their quantum computer (QC) with resounding success! It may enable much faster and better modelling of complex pharmaceutical designs, long-term weather forecasts or brain process simulations than classical computers. A 1,000-qubit QC can process in a single step 21000 possible superposition states: its speedup is exponential in the number of qubits. Yet this wondrous promise requires overcoming the enormous hurdle of decoherence, which is why progress towards a large-scale QC has been painstakingly slow. To their dismay, their QC is “expropriated for the quantum revolution” in order to share quantum information among all mankind and thus impose a collective entangled state of mind. They set out to foil this totalitarian plan and restore individuality by decohering the quantum information channel. The appendix to this chapter provide a flavor of QC capabilities through a quantum algorithm that can solve problems exponentially faster than classical computers.

scholarly journals Chemistry integrated circuit: chemical system on a complementary metal oxide semiconductor integrated circuit

2014 ◽  
Vol 372 (2012) ◽  
pp. 20130109 ◽  
Author(s):  
Kazuo Nakazato
Keyword(s):  
Integrated Circuit ◽  
High Speed ◽  
Large Scale ◽  
Sensor Array ◽  
Single Photon ◽  
Sensor Arrays ◽  
Oxide Semiconductor ◽  
Chemical System ◽  
Photoelectric Conversion ◽  
Integrated Sensor

By integrating chemical reactions on a large-scale integration (LSI) chip, new types of device can be created. For biomedical applications, monolithically integrated sensor arrays for potentiometric, amperometric and impedimetric sensing of biomolecules have been developed. The potentiometric sensor array detects pH and redox reaction as a statistical distribution of fluctuations in time and space. For the amperometric sensor array, a microelectrode structure for measuring multiple currents at high speed has been proposed. The impedimetric sensor array is designed to measure impedance up to 10 MHz. The multimodal sensor array will enable synthetic analysis and make it possible to standardize biosensor chips. Another approach is to create new functional devices by integrating molecular systems with LSI chips, for example image sensors that incorporate biological materials with a sensor array. The quantum yield of the photoelectric conversion of photosynthesis is 100%, which is extremely difficult to achieve by artificial means. In a recently developed process, a molecular wire is plugged directly into a biological photosynthetic system to efficiently conduct electrons to a gold electrode. A single photon can be detected at room temperature using such a system combined with a molecular single-electron transistor.

scholarly journals Characterizing large-scale quantum computers via cycle benchmarking

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Alexander Erhard ◽  
Joel J. Wallman ◽  
Lukas Postler ◽  
Michael Meth ◽  
Roman Stricker ◽  
...  
Keyword(s):  
Large Scale ◽  
Ion Trap ◽  
Quantum Computer ◽  
System Size ◽  
Quantum Computers ◽  
Large Set ◽  
Correlated Noise ◽  
Noise Sources ◽  
Total Process ◽  
Qubit Gate

AbstractQuantum computers promise to solve certain problems more efficiently than their digital counterparts. A major challenge towards practically useful quantum computing is characterizing and reducing the various errors that accumulate during an algorithm running on large-scale processors. Current characterization techniques are unable to adequately account for the exponentially large set of potential errors, including cross-talk and other correlated noise sources. Here we develop cycle benchmarking, a rigorous and practically scalable protocol for characterizing local and global errors across multi-qubit quantum processors. We experimentally demonstrate its practicality by quantifying such errors in non-entangling and entangling operations on an ion-trap quantum computer with up to 10 qubits, and total process fidelities for multi-qubit entangling gates ranging from $$99.6(1)\%$$99.6(1)% for 2 qubits to $$86(2)\%$$86(2)% for 10 qubits. Furthermore, cycle benchmarking data validates that the error rate per single-qubit gate and per two-qubit coupling does not increase with increasing system size.

Hidden symmetry detection on a quantum computer

2007 ◽  
Vol 7 (1&2) ◽  
pp. 83-92
Author(s):  
R. Schutzhold ◽  
W.G. Unruh
Keyword(s):  
Quantum Computer ◽  
Quantum Algorithms ◽  
Quantum Algorithm ◽  
Quantum Computers ◽  
Self Similarity ◽  
Hidden Subgroup Problem ◽  
Hidden Symmetry ◽  
Speed Up ◽  
Subgroup Problem ◽  
Discrete Scale

The fastest quantum algorithms (for the solution of classical computational tasks) known so far are basically variations of the hidden subgroup problem with {$f(U[x])=f(x)$}. Following a discussion regarding which tasks might be solved efficiently by quantum computers, it will be demonstrated by means of a simple example, that the detection of more general hidden (two-point) symmetries {$V\{f(x),f(U[x])\}=0$} by a quantum algorithm can also admit an exponential speed-up. E.g., one member of this class of symmetries {$V\{f(x),f(U[x])\}=0$} is discrete self-similarity (or discrete scale invariance).

scholarly journals A two-qubit photonic quantum processor and its application to solving systems of linear equations

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Stefanie Barz ◽  
Ivan Kassal ◽  
Martin Ringbauer ◽  
Yannick Ole Lipp ◽  
Borivoje Dakić ◽  
...  
Keyword(s):  
Large Scale ◽  
Linear Equations ◽  
Quantum Algorithm ◽  
Quantum Computers ◽  
Single Qubit ◽  
Quantum Processor ◽  
Systems Of Linear Equations ◽  
Significant Obstacle

Abstract Large-scale quantum computers will require the ability to apply long sequences of entangling gates to many qubits. In a photonic architecture, where single-qubit gates can be performed easily and precisely, the application of consecutive two-qubit entangling gates has been a significant obstacle. Here, we demonstrate a two-qubit photonic quantum processor that implements two consecutive CNOT gates on the same pair of polarisation-encoded qubits. To demonstrate the flexibility of our system, we implement various instances of the quantum algorithm for solving of systems of linear equations.

Gallium arsenide electronics in the marketplace

1992 ◽  
Vol 70 (10-11) ◽  
pp. 943-945
Author(s):  
Paul R. Jay.
Keyword(s):  
Gallium Arsenide ◽  
Integrated Circuits ◽  
Integrated Circuit ◽  
High Speed ◽  
Large Scale ◽  
Low Cost ◽  
Logic Gates ◽  
Process Technology ◽  
Maximum Benefit ◽  
Technological Developments

The last few years have seen a significant emergence of real product applications using gallium arsenide metal semi-conductor field effect transistor technology. These applications range from large volume consumer markets based on small low-cost GaAs integrated circuits to high-end supercomputer products using very large scale integrated GaAs chips containing up to 50 000 logic gates. This situation represents substantial advances in many areas: materials technology, device and integrated circuit process technology, packaging and high speed testing, as well as appropriate system design to obtain maximum benefit from the GaAs technology. This paper reviews some recent commercial successes, and considers commonalities existing between them in the context of recent technological developments.

scholarly journals Automated Quantum Hardware Selection for Quantum Workflows

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 984
Author(s):  
Benjamin Weder ◽  
Johanna Barzen ◽  
Frank Leymann ◽  
Marie Salm
Keyword(s):  
Quantum Computer ◽  
Quantum Algorithm ◽  
Software Tool ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Quantum Computers ◽  
Workflow Model ◽  
Selection For ◽  
Selection Of

The execution of a quantum algorithm typically requires various classical pre- and post-processing tasks. Hence, workflows are a promising means to orchestrate these tasks, benefiting from their reliability, robustness, and features, such as transactional processing. However, the implementations of the tasks may be very heterogeneous and they depend on the quantum hardware used to execute the quantum circuits of the algorithm. Additionally, today’s quantum computers are still restricted, which limits the size of the quantum circuits that can be executed. As the circuit size often depends on the input data of the algorithm, the selection of quantum hardware to execute a quantum circuit must be done at workflow runtime. However, modeling all possible alternative tasks would clutter the workflow model and require its adaptation whenever a new quantum computer or software tool is released. To overcome this problem, we introduce an approach to automatically select suitable quantum hardware for the execution of quantum circuits in workflows. Furthermore, it enables the dynamic adaptation of the workflows, depending on the selection at runtime based on reusable workflow fragments. We validate our approach with a prototypical implementation and a case study demonstrating the hardware selection for Simon’s algorithm.

scholarly journals Experimental pairwise entanglement estimation for an N-qubit system

2019 ◽  
Author(s):  
Elizabeth Behrman ◽  
Nathan Thompson ◽  
Nam Nguyen ◽  
James Steck
Keyword(s):  
Large Scale ◽  
Quantum Computer ◽  
Algorithm Design ◽  
Machine Learning Techniques ◽  
Quantum Computers ◽  
Entanglement Witness ◽  
Physical Computation ◽  
Learning Techniques ◽  
Qubit System ◽  
Computer Simulators

Designing and implementing algorithms for medium and large scale quantum computers is not easy. In previous work we have suggested, and developed, the idea of using machine learning techniques to train a quantum system such that the desired process is ``learned,'' thus obviating the algorithm design difficulty. This works quite well for small systems. But the goal is macroscopic physical computation. Here, we implement our learned pairwise entanglement witness on Microsoft's Q\#, one of the commercially available gate model quantum computer simulators; we perform statistical analysis to determine reliability and reproducibility; and we show that after training the system in stages for an incrementing number of qubits (2, 3, 4, \ldots) we can infer the pattern for mesoscopic $N$ from simulation results for three-, four-, five-, six-, and seven-qubit systems. Our results suggest a fruitful pathway for general quantum computer algorithm design and for practical computation on noisy intermediate scale quantum devices.

scholarly journals Decoherence in quantum walks and quantum computers

2008 ◽  
Vol 86 (4) ◽  
pp. 541-548 ◽  
Author(s):  
A P Hines ◽  
P C.E. Stamp
Keyword(s):  
Large Scale ◽  
Quantum Information Processing ◽  
Quantum Computer ◽  
Quantum Walks ◽  
Quantum Computers ◽  
Environment Interaction ◽  
Projective Measurement ◽  
Simplified Models ◽  
The Face ◽  
Open Question

Decoherence is the major stumbling block in the realization of a large-scale quantum computer. Ingenious methods have been devised to overcome decoherence, but their success has been proven only for over-simplified models of system-environment interaction. Whether such methods will be reliable in the face of more realistic models is a fundamental open question. In this partly pedagogical article, we study two toy models of quantum information processing, using the language of quantum walks. Decoherence is incorporated in three ways — by coupling to a noisy “projective measurement” system, and by coupling to oscillator and spin baths.PACS Nos.: 03.65.Yz, 03.67.Lx

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