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Adiabatic Quantum Computing for Binary Clustering [article]

Christian Bauckhage, Eduardo Brito, Kostadin Cvejoski, Cesar Ojeda, Rafet Sifa, Stefan Wrobel
2017 arXiv   pre-print
Quantum computing for machine learning attracts increasing attention and recent technological developments suggest that especially adiabatic quantum computing may soon be of practical interest.  ...  In this paper, we therefore consider this paradigm and discuss how to adopt it to the problem of binary clustering.  ...  the problem of k = 2-means clustering in terms of an Ising model that should allow for implementation on a D-Wave computer [4] , [5] 2) In sections V and VI, we show how to set our model up for adiabatic  ... 
arXiv:1706.05528v1 fatcat:jcyxw66eb5hz3pioa6lualqbaq

Chemical rate laws and rate constants

1998 Classical and Quantum Dynamics in Condensed Phase Simulations  
These expressions, while exact, are formidable to compute for a many-body quantum system.  ...  Following a discussion of the reduction of the full quantum dynamics to the adiabatic mixed quantum-classical limit, a description of proton transfer in a cluster composed of polar solvent molecules is  ...  To begin the analysis we rewrite the trace in the quantum expression for the rate kernel K(t) in Eq.  ... 
doi:10.1142/9789812839664_0024 fatcat:rhai4rm6ircodpepu3wwlscuuq

Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning [article]

Nico Piatkowski, Thore Gerlach, Romain Hugues, Rafet Sifa, Christian Bauckhage, Frederic Barbaresco
2022 arXiv   pre-print
To this end, k-medoids clustering, kernel density clustering, nearest neighbor search, and kernel methods are investigated and it is explained how these methods can be re-formulated for quantum annealers  ...  and gate-based quantum computers.  ...  For the first time, we combined these QUBO problems with quantum kernels, which combines the adiabatic quantum computing paradigm with quantum gate computing.  ... 
arXiv:2204.11133v1 fatcat:urcc7kpnnrcabfbmamcso4y6ky

Adiabatic Quantum Kitchen Sinks for Learning Kernels Using Randomized Features [article]

Moslem Noori, Seyed Shakib Vedaie, Inderpreet Singh, Daniel Crawford, Jaspreet S. Oberoi, Barry C. Sanders, Ehsan Zahedinejad
2019 arXiv   pre-print
While the race to build an error-corrected quantum computer is ongoing, noisy, intermediate-scale quantum (NISQ) devices provide an immediate platform for exploring a possible quantum advantage through  ...  One example of such a hybrid algorithm is "quantum kitchen sinks", which builds upon the classical algorithm known as "random kitchen sinks" to leverage a gate model quantum computer for machine learning  ...  Partial funding for this work was provided by the Mitacs Accelerate program. We thank Marko Bucyk for reviewing and editing the manuscript.  ... 
arXiv:1909.08131v1 fatcat:omn6ulxikjabbhf34ql5ppy7x4

Q-means using variational quantum feature embedding [article]

Arvind S Menon, Nikaash Puri
2021 arXiv   pre-print
a Variational quantum feature map and q-means as a subroutine for unsupervised learning.  ...  The output of the complete quantum circuit is used to compute the value of the cost function that is based on the Hilbert-Schmidt distance between the density matrices of the characteristic cluster quantum  ...  Other approaches such as adiabatic computing have been used as another method for K-means to find the best labelling possible for the encoded data, discussed in [3] .  ... 
arXiv:2112.05969v1 fatcat:xuy6awqm2bhsvni5tyhn37r3wi

Quantum-Assisted Clustering Algorithms for NISQ-Era Devices [article]

Samuel S. Mendelson, Robert W. Strand, Guy B. Oldaker IV, Jacob M. Farinholt
2019 arXiv   pre-print
In the NISQ-era of quantum computing, we should not expect to see quantum devices that provide an exponential improvement in runtime for practical problems, due to the lack of error correction and small  ...  In this article, we develop several hybrid quantum-classical clustering algorithms that can be employed as subroutines on small, NISQ-era devices.  ...  The authors are particularly grateful for useful discussions and insights provided by Dave Marchette and the rest of the members of the AM&DA group.  ... 
arXiv:1904.08992v3 fatcat:k7jdazrejndkpm2tkq7u6fdcd4

An introduction to quantum machine learning

Maria Schuld, Ilya Sinayskiy, Francesco Petruccione
2014 Contemporary physics (Print)  
In the last couple of years, researchers investigated if quantum computing can help to improve classical machine learning algorithms.  ...  Ideas range from running computationally costly algorithms or their subroutines efficiently on a quantum computer to the translation of stochastic methods into the language of quantum theory.  ...  This is why we want to sketch the idea of how to use adiabatic quantum computing for k-means clustering.  ... 
doi:10.1080/00107514.2014.964942 fatcat:bow7e3mhqbavllfjxoskazi2ey


Raymond KAPRAL, Styliani CONSTA
2002 Chemistry education  
The free energy profile along this RC for a cluster that consists of 180 water molecules and 4 Na + is shown in Fig. 2 .  ...  FIGURE 2: Free energy (reversible work) profile (solid line) for a cluster with 180 water molecules that contain 4 Na + ions.  ... 
doi:10.1039/b2rp90019j fatcat:s3kaz26tiracpgtkuqc4lcb6qm

An Investigation of Quantum Deep Clustering Framework with Quantum Deep SVM Convolutional Neural Network Feature Extractor [article]

Arit Kumar Bishwas, Ashish Mani, Vasile Palade
2019 arXiv   pre-print
quantum K-Means clustering.  ...  We have investigated the run time computational complexity of the proposed quantum deep clustering framework and compared with the possible classical implementation.  ...  We also replace the classical K-Means clustering algorithm with a quantum version of the -Means clustering algorithm.  ... 
arXiv:1909.09852v1 fatcat:pq6awtucjbgh7a53xzrquu2yum

Bistability in a nonequilibrium quantum system with electron-phonon interactions

Eli Y. Wilner, Haobin Wang, Guy Cohen, Michael Thoss, Eran Rabani
2013 Physical Review B  
Considering a generic model for quantum transport through a quantum dot with electron-phonon interaction, we prove that a unique steady-state exists regardless of the initial electronic preparation of  ...  However, a bistability can be observed for different initial phonon preparations.  ...  This work was supported by the FP7 Marie Curie IOF project HJSC, by the DFG (SFB 953 and cluster of excellence EAM), and used resources of the National Energy Research Scientific Computing Center, which  ... 
doi:10.1103/physrevb.88.045137 fatcat:jtrgwpwkjzcsld3phqnyil7die

Spectral signatures of the Luttinger liquid to the charge-density-wave transition

M. Hohenadler, G. Wellein, A. R. Bishop, A. Alvermann, H. Fehske
2006 Physical Review B  
The results obtained by means of kernel polynomial and systematic cluster approaches reveal substantially different physics in these regimes and further indicate that the size of the phonon frequency significantly  ...  affects the nature of the quantum Peierls phase transition.  ...  In contrast to the adiabatic case of Fig. 3͑a͒, Fig. 3͑c͒ shows a clear gap for all k.  ... 
doi:10.1103/physrevb.73.245120 fatcat:ous6xuuh2bgvpbaiw6o3u3uud4

Towards TDDFT for Strongly Correlated Materials

Shree Acharya, Volodymyr Turkowski, Talat Rahman
2016 Computation  
We conclude by proposing an algorithm for the generalization of the theory to non-linear response. Computation 2016, 4, 34 2 of 20 purposes mentioned above.  ...  We proceed with deriving the expression for the XC kernel for the one-band Hubbard model by solving DMFT equations via two approaches, the Hirsch-Fye Quantum Monte Carlo (HF-QMC) and an approximate low-cost  ...  Comparison of our results for the XC kernel with another available rare result for the frequency-dependent XC kernel for strongly-correlated systems, namely for a cubic 3 × 3 cluster [14] , shows that  ... 
doi:10.3390/computation4030034 fatcat:n5354bhvmvc3piqmfiyijbpylq

Universality of entanglement and quantum-computation complexity

Román Orús, José I. Latorre
2004 Physical Review A. Atomic, Molecular, and Optical Physics  
We study the universality of scaling of entanglement in Shor's factoring algorithm and in adiabatic quantum algorithms across a quantum phase transition for both the NP-complete Exact Cover problem as  ...  A similar result is obtained numerically for the quantum adiabatic evolution Exact Cover algorithm, which also shows universality of the quantum phase transition the system evolves nearby.  ...  Part of this work was done at the Benasque Center for Science.  ... 
doi:10.1103/physreva.69.052308 fatcat:cnwmk6sksbbuxjhmcq44rwcauq

Adiabatic Quantum Linear Regression [article]

Prasanna Date, Thomas Potok
2020 arXiv   pre-print
In this paper, we present an adiabatic quantum computing approach for training a linear regression model.  ...  We analyze our quantum approach theoretically, test it on the D-Wave 2000Q adiabatic quantum computer and compare its performance to a classical approach that uses the Scikit-learn library in Python.  ...  The Scikitlearn library is widely used for machine learning tasks like linear regression, support vector machines, K-nearest neighbors, K-means clustering etc.  ... 
arXiv:2008.02355v1 fatcat:ivvhvclcdralbf4yrz7krthg44

Classical Equivalent Quantum Unsupervised Learning Algorithms

Prakhar Shrivastava, Kapil Kumar Soni, Akhtar Rasool
2020 Procedia Computer Science  
analysis and achieved computational speedup and show processing such problems over quantum machines.  ...  The and dimensionality reduction are used for data smoothing to predict best possible outcome as per the analysis.  ...  Quantum methodology Optimizing the K-Median problem is NP-hard for all K2.  ... 
doi:10.1016/j.procs.2020.03.204 fatcat:244jo75gnbcwnhtlkbve27syee
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