Quantum natural language processing

Short description: Quantum computing applied to natural language processing

Quantum natural language processing (QNLP) is the application of quantum computing to natural language processing (NLP). It computes word embeddings as parameterised quantum circuits that can solve NLP tasks faster than any classical computer.[1][2][3] It is inspired by categorical quantum mechanics and the DisCoCat framework, making use of string diagrams to translate from grammatical structure to quantum processes.[4][5][6]

## Contents

* 1 Theory
* 2 Experiments
* 3 See also
* 4 References
* 5 External links

## Theory

The first quantum algorithm for natural language processing used the DisCoCat framework and Grover's algorithm to show a quadratic quantum speedup for a text classification task.[1] It was later shown that quantum language processing is BQP-Complete,[2] i.e. quantum language models are more expressive than their classical counterpart, unless quantum mechanics can be efficiently simulated by classical computers.[7]

These two theoretical results assume fault-tolerant quantum computation and a QRAM, i.e. an efficient way to load classical data on a quantum computer. Thus, they are not applicable to the noisy intermediate-scale quantum (NISQ) computers available today.

## Experiments

The algorithm of Zeng and Coecke[1] was adapted to the constraints of NISQ computers and implemented on IBM quantum computers to solve binary classification tasks.[8][9] Instead of loading classical word vectors onto a quantum memory, the word vectors are computed directly as the parameters of quantum circuits. These parameters are optimised using methods from quantum machine learning to solve data-driven tasks such as question answering,[8] machine translation[10] and even algorithmic music composition.[11]

## See also

* Categorical quantum mechanics
* Natural language processing
* Quantum machine learning
* Applied category theory
* String diagram

## References

1. ↑ 1.0 1.1 1.2 Zeng, William; Coecke, Bob (2016-08-02). "Quantum Algorithms for Compositional Natural Language Processing". Electronic Proceedings in Theoretical Computer Science 221: 67–75. doi:10.4204/EPTCS.221.8. ISSN 2075-2180.
2. ↑ 2.0 2.1 Wiebe, Nathan; Bocharov, Alex; Smolensky, Paul; Troyer, Matthias; Svore, Krysta M. (2019-02-13). "Quantum Language Processing". arXiv:1902.05162 [quant-ph].
3. ↑ Rai, Anshuman (2022-01-31). "A Review Article on Quantum Natural Language Processing". International Journal for Research in Applied Science and Engineering Technology 10 (1): 1588–1594. doi:10.22214/ijraset.2022.40103. ISSN 2321-9653.
4. ↑ Rai, Anshuman (2022-01-31). "A Review Article on Quantum Natural Language Processing". International Journal for Research in Applied Science and Engineering Technology 10 (1): 1588–1594. doi:10.22214/ijraset.2022.40103. ISSN 2321-9653.
5. ↑ Coecke, Bob; de Felice, Giovanni; Meichanetzidis, Konstantinos; Toumi, Alexis (2020-12-07). "Foundations for Near-Term Quantum Natural Language Processing". arXiv:2012.03755 [quant-ph].
6. ↑ Ganguly, Srinjoy; Morapakula, Sai Nandan; Bertel, Luis Gerardo Ayala, "An Introduction to Quantum Natural Language Processing (QNLP)", Coded Leadership (CRC Press): pp. 1–23, https://scholar.googleusercontent.com/scholar.bib?q=info:99vJ3qI5weYJ:scholar.google.com/&output=citation&scisdr=CgXXiV6NEJT6ufh-l8c:AAGBfm0AAAAAY254j8e-YvWJCbzzeSdNy6zX622uwnCR&scisig=AAGBfm0AAAAAY254j4Qs1327jYdk7IWvqLxtBWeyj91O&scisf=4&ct=citation&cd=-1&hl=en, retrieved 2022-11-11
7. ↑ Rai, Anshuman (2022-01-31). "A Review Article on Quantum Natural Language Processing". International Journal for Research in Applied Science and Engineering Technology 10 (1): 1588–1594. doi:10.22214/ijraset.2022.40103. ISSN 2321-9653.
8. ↑ 8.0 8.1 Meichanetzidis, Konstantinos; Toumi, Alexis; de Felice, Giovanni; Coecke, Bob (2023). "Grammar-aware sentence classification on quantum computers". Quantum Machine Intelligence 5. doi:10.1007/s42484-023-00097-1.
9. ↑ Lorenz, Robin; Pearson, Anna; Meichanetzidis, Konstantinos; Kartsaklis, Dimitri; Coecke, Bob (2023). "QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer". Journal of Artificial Intelligence Research 76: 1305–1342. doi:10.1613/jair.1.14329.
10. ↑ Vicente Nieto, Irene (2021). Towards Machine Translation with Quantum Computers. Master thesis, Stockholm University, Faculty of Science, Department of Physics.. https://www.diva-portal.org/smash/get/diva2:1592369/FULLTEXT01.pdf.
11. ↑ Miranda, Eduardo Reck; Yeung, Richie; Pearson, Anna; Meichanetzidis, Konstantinos; Coecke, Bob (2022), Miranda, Eduardo Reck, ed., "A Quantum Natural Language Processing Approach to Musical Intelligence" (in en), Quantum Computer Music: Foundations, Methods and Advanced Concepts (Cham: Springer International Publishing): pp. 313–356, doi:10.1007/978-3-031-13909-3_13, ISBN 978-3-031-13909-3, https://doi.org/10.1007/978-3-031-13909-3_13, retrieved 2022-11-07

## External links

* DisCoPy, a Python toolkit for computing with string diagrams
* lambeq, a Python library for quantum natural language processing
* FQF, Operational protocol applying QNLP to forensic philology

* v
* t
* e

Quantum information science

General|

* Quantum computing
* Qubit
* physical vs. logical
* DiVincenzo's criteria
* Quantum information
* Quantum programming
* Quantum processors
* Cloud-based quantum computing
* Timeline of quantum computing

Theorems|

* Bell's theorem
* Gleason's theorem
* Gottesman–Knill theorem
* Holevo's theorem
* Margolus–Levitin theorem
* No-broadcast theorem
* No-cloning theorem
* No-communication theorem
* No-deleting theorem
* No-hiding theorem
* No-teleportation theorem
* PBR theorem
* Quantum threshold theorem

Quantum
communication|

* Quantum capacity
* Classical capacity
* Entanglement-assisted classical capacity
* Quantum channel
* Quantum network
* Quantum cryptography
* Quantum key distribution
* BB84
* SARG04
* Three-stage quantum cryptography protocol
* Quantum teleportation
* Superdense coding
* LOCC
* Entanglement distillation

Quantum algorithms|

* Universal quantum simulator
* Deutsch–Jozsa algorithm
* Grover's algorithm
* Quantum Fourier transform
* Shor's algorithm
* Simon's problem
* Quantum phase estimation algorithm
* Quantum counting algorithm
* Quantum annealing
* Quantum algorithm for linear systems of equations
* Amplitude amplification

Quantum
complexity theory|

* Quantum Turing machine
* EQP
* BQP
* QMA
* PostBQP
* QIP

Quantum
computing models|

* Quantum circuit
* Quantum logic gate
* One-way quantum computer
* cluster state
* Adiabatic quantum computation
* Topological quantum computer

Quantum
error correction|

* Stabilizer codes
* Entanglement-Assisted Quantum Error Correction
* Shor code
* Steane code
* CSS code
* Quantum convolutional codes
* Toric code

Physical
implementations|

| Quantum optics|

* Cavity QED
* Circuit QED
* Linear optical quantum computing
* KLM protocol
* Boson sampling

|

Ultracold atoms|

* Trapped ion quantum computer
* Optical lattice

Spin-based|

* Nuclear magnetic resonance QC
* Kane QC
* Loss–DiVincenzo QC
* Nitrogen-vacancy center

Superconducting
quantum computing|

* Charge qubit
* Flux qubit
* Phase qubit
* Transmon

Software|

* libquantum
* OpenQASM
* Q#
* Qiskit
* IBM Q Experience

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