ZX-calculus

Last updated

The ZX-calculus is a rigorous graphical language for reasoning about linear maps between qubits, which are represented as string diagrams called ZX-diagrams. A ZX-diagram consists of a set of generators called spiders that represent specific tensors. These are connected together to form a tensor network similar to Penrose graphical notation. Due to the symmetries of the spiders and the properties of the underlying category, topologically deforming a ZX-diagram (i.e. moving the generators without changing their connections) does not affect the linear map it represents. In addition to the equalities between ZX-diagrams that are generated by topological deformations, the calculus also has a set of graphical rewrite rules for transforming diagrams into one another. The ZX-calculus is universal in the sense that any linear map between qubits can be represented as a diagram, and different sets of graphical rewrite rules are complete for different families of linear maps. ZX-diagrams can be seen as a generalisation of quantum circuit notation, and they form a strict subset of tensor networks which represent general fusion categories and wavefunctions of quantum spin systems.

Contents

History

The ZX-calculus was first introduced by Bob Coecke and Ross Duncan in 2008 as an extension of the categorical quantum mechanics school of reasoning. They introduced the fundamental concepts of spiders, strong complementarity and most of the standard rewrite rules. [1] [2]

In 2009 Duncan and Perdrix found the additional Euler decomposition rule for the Hadamard gate, [3] which was used by Backens in 2013 to establish the first completeness result for the ZX-calculus. [4] Namely that there exists a set of rewrite rules that suffice to prove all equalities between stabilizer ZX-diagrams, where phases are multiples of , up to global scalars. This result was later refined to completeness including scalar factors. [5]

Following an incompleteness result, [6] in 2017, a completion of the ZX-calculus for the approximately universal fragment was found, [7] in addition to two different completeness results for the universal ZX-calculus (where phases are allowed to take any real value). [8] [9]

Also in 2017 the book Picturing Quantum Processes was released, that builds quantum theory from the ground up, using the ZX-calculus. [10] See also the 2019 book Categories for Quantum Theory. [11]

Informal introduction

An example ZX-diagram. This one has two inputs (wires coming from the left), and three outputs (wires exiting to the right), and hence it represents a linear map from
C
2
2
{\displaystyle \mathbb {C} ^{2^{2}}}
to
C
2
3
{\displaystyle \mathbb {C} ^{2^{3}}}
. Zx-diagram-example.svg
An example ZX-diagram. This one has two inputs (wires coming from the left), and three outputs (wires exiting to the right), and hence it represents a linear map from to .

ZX-diagrams consist of green and red nodes called spiders, which are connected by wires. Wires may curve and cross, arbitrarily many wires may connect to the same spider, and multiple wires can go between the same pair of nodes. There are also Hadamard nodes, usually denoted by a yellow box, which always connect to exactly two wires.

ZX-diagrams represent linear maps between qubits, similar to the way in which quantum circuits represent unitary maps between qubits. ZX-diagrams differ from quantum circuits in two main ways. The first is that ZX-diagrams do not have to conform to the rigid topological structure of circuits, and hence can be deformed arbitrarily. The second is that ZX-diagrams come equipped with a set of rewrite rules, collectively referred to as the ZX-calculus. Using these rules, calculations can be performed in the graphical language itself.

Generators

The building blocks or generators of the ZX-calculus are graphical representations of specific states, unitary operators, linear isometries, and projections in the computational basis and the Hadamard-transformed basis and . The colour green (or sometimes white) is used to represent the computational basis and the colour red (or sometimes grey) is used to represent the Hadamard-transformed basis. Each of these generators can furthermore be labelled by a phase, which is a real number from the interval . If the phase is zero it is usually not written.

The generators are:

ZX-calculus generators, informally
TypeGeneratorCorresponding linear mapRemarks
state ZX-calculus green state.svg For and , this map corresponds to unnormalised versions of the Hadamard-transformed basis states and , respectively. For , this is an unnormalised version of the T magic state [12] .
state ZX-calculus red state.svg For and , this map corresponds to unnormalised versions of the computational basis states and , respectively.
unitary map ZX-calculus green phase shift.svg This map is a rotation about the Z-axis of the Bloch sphere by an angle . For , it is the Z Pauli matrix.
unitary map ZX-calculus red phase shift.svg This map is a rotation about the X-axis of the Bloch sphere by an angle . For , it is the X Pauli matrix.
unitary map
Zx-calculus yellow Hadamard gate.svg
This map is the Hadamard gate often used in quantum circuits.
isometry ZX-calculus green copy map.svg For , this map represents a copy operation in the computational basis. For the same value of , it also corresponds to the smooth split operation of lattice surgery. [13]
isometry ZX-calculus red copy map.svg For , this map represents a copy operation in the Hadamard-transformed basis. For the same value of , it also corresponds to the rough split operation of lattice surgery. [13]
partial isometry ZX-calculus green co-copy map.svg For , this map represents a controlled-NOT operation followed by a destructive Z measurement on the target qubit post-selected to the state . For the same value of , it also corresponds to the smooth merge (without byproduct operators) of lattice surgery. [13]
partial isometry ZX-calculus red co-copy map.svg For , this map represents a controlled-NOT operation followed by a destructive X measurement on the control qubit post-selected to the state . For the same value of , it also corresponds to the rough merge (without byproduct operators) of lattice surgery. [13]
projection ZX-calculus green effect.svg For or , this map corresponds to a destructive X measurement post-selected to the state or , respectively.
projection ZX-calculus red effect.svg For or , this map corresponds to a destructive Z measurement post-selected to the state or , respectively.

Composition

The generators can be composed in two ways:

These laws correspond to the composition and tensor product of linear maps.

Any diagram written by composing generators in this way is called a ZX-diagram. ZX-diagrams are closed under both composition laws: connecting an output of one ZX-diagram to an input of another creates a valid ZX-diagram, and vertically stacking two ZX-diagrams creates a valid ZX-diagram.

Only topology matters

Two diagrams represent the same linear operator if they consist of the same generators connected in the same ways. In other words, whenever two ZX-diagrams can be transformed into one another by topological deformation, then they represent the same linear map. Thus, the controlled-NOT gate can be represented as follows:

ZX-calculus cNOT-example.svg

Diagram rewriting

The following example of a quantum circuit constructs a GHZ-state. By translating it into a ZX-diagram, using the rules that "adjacent spiders of the same color merge", "Hadamard changes the color of spiders", and "parity-2 spiders are identities", it can be graphically reduced to a GHZ-state:

GHZ circuit as ZX-diagram.svg

Any linear map between qubits can be represented as a ZX-diagram, i.e. ZX-diagrams are universal. A given ZX-diagram can be transformed into another ZX-diagram using the rewrite rules of the ZX-calculus if and only if the two diagrams represent the same linear map, i.e. the ZX-calculus is sound and complete.

Formal definition

The category of ZX-diagrams is a dagger compact category, which means that it has symmetric monoidal structure (a tensor product), is compact closed (it has cups and caps) and comes equipped with a dagger, such that all these structures suitably interact. The objects of the category are the natural numbers, with the tensor product given by addition (the category is a PROP). The morphisms of this category are ZX-diagrams. Two ZX-diagrams compose by juxtaposing them horizontally and connecting the outputs of the left-hand diagram to the inputs of the right-hand diagram. The monoidal product of two diagrams is represented by placing one diagram above the other.

Indeed, all ZX-diagrams are built freely from a set of generators via composition and monoidal product, modulo the equalities induced by the compact structure and the rules of the ZX-calculus given below. For instance, the identity of the object is depicted as parallel wires from left to right, with the special case being the empty diagram.

The following table gives the generators together with their standard interpretations as linear maps, expressed in Dirac notation. The computational basis states are denoted by and the Hadamard-transformed basis states are . The -fold tensor-product of the vector is denoted by .

Generators of ZX-diagrams [14]
NameDiagramTypeLinear map it represents
empty diagram
This is the common representation for an empty diagram in categorical quantum mechanics Categorical quantum mechanics empty diagram.svg
This is the common representation for an empty diagram in categorical quantum mechanics
1
wire/identity
Bell state
This is the common representation for a cup diagram in categorical quantum mechanics Categorical quantum mechanics cup.svg
This is the common representation for a cup diagram in categorical quantum mechanics
Bell effect
This is the common representation for a cap in categorical quantum mechanics Categorical quantum mechanics cap.svg
This is the common representation for a cap in categorical quantum mechanics
swap
This is the common representation of the swap morphism in the graphical language of symmetric monoidal categories Symmetric monoidal category swap.svg
This is the common representation of the swap morphism in the graphical language of symmetric monoidal categories
Z spider
This is the green Z-spider from the ZX-calculus, with a phase alpha and n inputs and m outputs Zx-calculus green phase spider with n inputs and m outputs.svg
This is the green Z-spider from the ZX-calculus, with a phase alpha and n inputs and m outputs
X spider
This is the red X-spider from the ZX-calculus, with a phase alpha and n inputs and m outputs Zx-calculus red phase spider with n inputs and m outputs.svg
This is the red X-spider from the ZX-calculus, with a phase alpha and n inputs and m outputs
Hadamard
This is the standard yellow representation of a Hadamard gate in the ZX-calculus Zx-calculus yellow Hadamard gate.svg
This is the standard yellow representation of a Hadamard gate in the ZX-calculus

There are many different versions of the ZX-calculus, using different systems of rewrite rules as axioms. All share the meta rule "only the topology matters", which means that two diagrams are equal if they consist of the same generators connected in the same way, no matter how these generators are arranged in the diagram. The following are some of the core set of rewrite rules, here given "up to scalar factor": i.e. two diagrams are considered to be equal if their interpretations as linear maps differ by a non-zero complex factor.

Rules of the ZX-calculus [15]
Rule nameRuleDescription
Z-spider fusion ZX-calculus green spider fusion rule.svg Whenever two Z-spider touch, then can fuse together, and their phases add. This rule corresponds to the fact that the Z-spider represents an orthonormal basis - the computational basis.
X-spider fusion ZX-calculus red spider fusion rule.svg See Z-spider fusion.
Identity rule
ZX-calculus red and green identity rules.svg
A phaseless arity 2 Z- or X-spider is equal to the identity. This rule states that the Bell-state is the same whether expressed in the computational basis or the Hadamard-transformed basis. In category-theoretic terms it says that the compact structure induced by the Z- and X-spider coincide.
Color change
ZX-calculus colour change rule.svg
The Hadamard-gate changes the color of spiders. This expresses the property that the Hadamard gate maps between the computational basis and the Hadamard-transformed basis.
Copy rule
ZX-calculus 2 output red-green copy rule.svg
A Z-spider copies arity-1 X-spiders. This expresses the fact that an arity-1 X-spider is proportional to a computational basis state (in this case ).
Bialgebra rule ZX-calculus 2 input 2 output bialgebra rule.svg A 2-cycle of Z- and X-spiders simplifies. This expresses the property that the computational basis and the Hadamard-transformed basis are strongly complementary.
-copy rule ZX-calculus red pi trough green phase spider copy rule.svg A NOT-gate (an arity-2 X-spider with a phase) copies through a Z-spider, and flips the phase of this spider. This rule states two properties at once. First, that NOT is a function map of the computational basis (it maps basis states to basis states), and second that when a NOT is commuted through a Z-rotation gate, that this rotation flips.
Euler decomposition ZX-calculus Hadamard scalar-free Euler decomposition rule.svg A Hadamard-gate can be expanded into three rotations around the Bloch sphere (corresponding to its Euler angles). Sometimes this rule is taken as the definition of the Hadamard generator, in which case the only generators of ZX-diagrams are the Z- and X-spider.

Applications

The ZX-calculus has been used in a variety of quantum information and computation tasks.

Tools

The rewrite rules of the ZX-calculus can be implemented formally as an instance of double-pushout rewriting. This has been used in the software Quantomatic to allow automated rewriting of ZX-diagrams (or more general string diagrams). [24] In order to formalise the usage of the "dots" to denote any number of wires, such as used in the spider fusion rule, this software uses bang-box notation [25] to implement rewrite rules where the spiders can have any number of inputs or outputs.

A more recent project to handle ZX-diagrams is PyZX, which is primarily focused on circuit optimisation. [15]

A LaTeX package zx-calculus can be used to typeset ZX-diagrams. Many authors also use the software TikZiT as a GUI to help typeset diagrams.

The ZX-calculus is only one of several graphical languages for describing linear maps between qubits. The ZW-calculus was developed alongside the ZX-calculus, and can naturally describe the W-state and Fermionic quantum computing. [26] [27] It was the first graphical language which had a complete rule-set for an approximately universal set of linear maps between qubits, [8] and the early completeness results of the ZX-calculus use a reduction to the ZW-calculus.

A more recent language is the ZH-calculus. This adds the H-box as a generator, that generalizes the Hadamard gate from the ZX-calculus. It can naturally describe quantum circuits involving Toffoli gates. [28]

Up to scalars, the phase-free ZX-calculus, generated by -labelled spiders is equivalent to the dagger compact closed category of linear relations over the finite field . In other words, given a diagram with inputs and outputs in the phase-free ZX-calculus, its X stabilizers form a linear subspace of , and the composition of phase-free ZX diagrams corresponds to relational composition of these subspaces. In particular, the Z comonoid (given by the Z spider with one input and two outputs, and the Z spider with one input and no outputs) and X monoid (given by the X spider with one output and two inputs, and the X spider with one output and no inputs) generate the symmetric monoidal category of matrices over with respect to the direct sum as the monoidal product.

See also

Related Research Articles

In physics, the no-cloning theorem states that it is impossible to create an independent and identical copy of an arbitrary unknown quantum state, a statement which has profound implications in the field of quantum computing among others. The theorem is an evolution of the 1970 no-go theorem authored by James Park, in which he demonstrates that a non-disturbing measurement scheme which is both simple and perfect cannot exist. The aforementioned theorems do not preclude the state of one system becoming entangled with the state of another as cloning specifically refers to the creation of a separable state with identical factors. For example, one might use the controlled NOT gate and the Walsh–Hadamard gate to entangle two qubits without violating the no-cloning theorem as no well-defined state may be defined in terms of a subsystem of an entangled state. The no-cloning theorem concerns only pure states whereas the generalized statement regarding mixed states is known as the no-broadcast theorem.

<span class="mw-page-title-main">Quantum computing</span> Technology that uses quantum mechanics

A quantum computer is a computer that exploits quantum mechanical phenomena. On small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior using specialized hardware. Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster than any modern "classical" computer. In particular, a large-scale quantum computer could break widely used encryption schemes and aid physicists in performing physical simulations; however, the current state of the art is largely experimental and impractical, with several obstacles to useful applications.

<span class="mw-page-title-main">Qubit</span> Basic unit of quantum information

In quantum computing, a qubit or quantum bit is a basic unit of quantum information—the quantum version of the classic binary bit physically realized with a two-state device. A qubit is a two-state quantum-mechanical system, one of the simplest quantum systems displaying the peculiarity of quantum mechanics. Examples include the spin of the electron in which the two levels can be taken as spin up and spin down; or the polarization of a single photon in which the two spin states can also be measured as horizontal and vertical linear polarization. In a classical system, a bit would have to be in one state or the other. However, quantum mechanics allows the qubit to be in a coherent superposition of multiple states simultaneously, a property that is fundamental to quantum mechanics and quantum computing.

<span class="mw-page-title-main">Quantum circuit</span> Model of quantum computing

In quantum information theory, a quantum circuit is a model for quantum computation, similar to classical circuits, in which a computation is a sequence of quantum gates, measurements, initializations of qubits to known values, and possibly other actions. The minimum set of actions that a circuit needs to be able to perform on the qubits to enable quantum computation is known as DiVincenzo's criteria.

<span class="mw-page-title-main">Quantum logic gate</span> Basic circuit in quantum computing

In quantum computing and specifically the quantum circuit model of computation, a quantum logic gate is a basic quantum circuit operating on a small number of qubits. Quantum logic gates are the building blocks of quantum circuits, like classical logic gates are for conventional digital circuits.

Quantum error correction (QEC) is a set of techniques used in quantum computing to protect quantum information from errors due to decoherence and other quantum noise. Quantum error correction is theorised as essential to achieve fault tolerant quantum computing that can reduce the effects of noise on stored quantum information, faulty quantum gates, faulty quantum state preparation, and faulty measurements. Effective quantum error correction would allow quantum computers with low qubit fidelity to execute algorithms of higher complexity or greater circuit depth.

<span class="mw-page-title-main">Controlled NOT gate</span> Quantum logic gate

In computer science, the controlled NOT gate, controlled-X gate, controlled-bit-flip gate, Feynman gate or controlled Pauli-X is a quantum logic gate that is an essential component in the construction of a gate-based quantum computer. It can be used to entangle and disentangle Bell states. Any quantum circuit can be simulated to an arbitrary degree of accuracy using a combination of CNOT gates and single qubit rotations. The gate is sometimes named after Richard Feynman who developed an early notation for quantum gate diagrams in 1986.

BB84 is a quantum key distribution scheme developed by Charles Bennett and Gilles Brassard in 1984. It is the first quantum cryptography protocol. The protocol is provably secure assuming a perfect implementation, relying on two conditions: (1) the quantum property that information gain is only possible at the expense of disturbing the signal if the two states one is trying to distinguish are not orthogonal ; and (2) the existence of an authenticated public classical channel. It is usually explained as a method of securely communicating a private key from one party to another for use in one-time pad encryption. The proof of BB84 depends on a perfect implementation. Side channel attacks exist, taking advantage of non-quantum sources of information. Since this information is non-quantum, it can be intercepted without measuring or cloning quantum particles.

<span class="mw-page-title-main">One-way quantum computer</span> Method of quantum computing

The one-way quantum computer, also known as measurement-based quantum computer (MBQC), is a method of quantum computing that first prepares an entangled resource state, usually a cluster state or graph state, then performs single qubit measurements on it. It is "one-way" because the resource state is destroyed by the measurements.

In quantum information and quantum computing, a cluster state is a type of highly entangled state of multiple qubits. Cluster states are generated in lattices of qubits with Ising type interactions. A cluster C is a connected subset of a d-dimensional lattice, and a cluster state is a pure state of the qubits located on C. They are different from other types of entangled states such as GHZ states or W states in that it is more difficult to eliminate quantum entanglement in the case of cluster states. Another way of thinking of cluster states is as a particular instance of graph states, where the underlying graph is a connected subset of a d-dimensional lattice. Cluster states are especially useful in the context of the one-way quantum computer. For a comprehensible introduction to the topic see.

SARG04 is a 2004 quantum cryptography protocol derived from the first protocol of that kind, BB84.

Categorical quantum mechanics is the study of quantum foundations and quantum information using paradigms from mathematics and computer science, notably monoidal category theory. The primitive objects of study are physical processes, and the different ways that these can be composed. It was pioneered in 2004 by Samson Abramsky and Bob Coecke. Categorical quantum mechanics is entry 18M40 in MSC2020.

In quantum computing, the quantum Fourier transform (QFT) is a linear transformation on quantum bits, and is the quantum analogue of the discrete Fourier transform. The quantum Fourier transform is a part of many quantum algorithms, notably Shor's algorithm for factoring and computing the discrete logarithm, the quantum phase estimation algorithm for estimating the eigenvalues of a unitary operator, and algorithms for the hidden subgroup problem. The quantum Fourier transform was discovered by Don Coppersmith. With small modifications to the QFT, it can also be used for performing fast integer arithmetic operations such as addition and multiplication.

Linear optical quantum computing or linear optics quantum computation (LOQC), also photonic quantum computing (PQC), is a paradigm of quantum computation, allowing (under certain conditions, described below) universal quantum computation. LOQC uses photons as information carriers, mainly uses linear optical elements, or optical instruments (including reciprocal mirrors and waveplates) to process quantum information, and uses photon detectors and quantum memories to detect and store quantum information.

The KLM scheme or KLM protocol is an implementation of linear optical quantum computing (LOQC) developed in 2000 by Emanuel Knill, Raymond Laflamme and Gerard J. Milburn. This protocol allows for the creation of universal quantum computers using solely linear optical tools. The KLM protocol uses linear optical elements, single-photon sources and photon detectors as resources to construct a quantum computation scheme involving only ancilla resources, quantum teleportations and error corrections.

<span class="mw-page-title-main">Bernstein–Vazirani algorithm</span> Quantum algorithm

The Bernstein–Vazirani algorithm, which solves the Bernstein–Vazirani problem, is a quantum algorithm invented by Ethan Bernstein and Umesh Vazirani in 1997. It is a restricted version of the Deutsch–Jozsa algorithm where instead of distinguishing between two different classes of functions, it tries to learn a string encoded in a function. The Bernstein–Vazirani algorithm was designed to prove an oracle separation between complexity classes BQP and BPP.

<span class="mw-page-title-main">Swap test</span> Technique for comparing quantum states

The swap test is a procedure in quantum computation that is used to check how much two quantum states differ, appearing first in the work of Barenco et al. and later rediscovered by Harry Buhrman, Richard Cleve, John Watrous, and Ronald de Wolf. It appears commonly in quantum machine learning, and is a circuit used for proofs-of-concept in implementations of quantum computers.

Parity measurement is a procedure in quantum information science used for error detection in quantum qubits. A parity measurement checks the equality of two qubits to return a true or false answer, which can be used to determine whether a correction needs to occur. Additional measurements can be made for a system greater than two qubits. Because parity measurement does not measure the state of singular bits but rather gets information about the whole state, it is considered an example of a joint measurement. Joint measurements do not have the consequence of destroying the original state of a qubit as normal quantum measurements do. Mathematically speaking, parity measurements are used to project a state into an eigenstate of an operator and to acquire its eigenvalue.

DisCoCat is a mathematical framework for natural language processing which uses category theory to unify distributional semantics with the principle of compositionality. The grammatical derivations in a categorial grammar are interpreted as linear maps acting on the tensor product of word vectors to produce the meaning of a sentence or a piece of text. String diagrams are used to visualise information flow and reason about natural language semantics.

In the mathematical field of category theory, FinVect is the category whose objects are all finite-dimensional vector spaces and whose morphisms are all linear maps between them.

References

  1. Coecke, Bob; Duncan, Ross (2008), "Interacting Quantum Observables", Automata, Languages and Programming, Lecture Notes in Computer Science, vol. 5126, Springer Berlin Heidelberg, pp. 298–310, CiteSeerX   10.1.1.381.2573 , doi:10.1007/978-3-540-70583-3_25, ISBN   9783540705826
  2. Coecke, Bob; Duncan, Ross (2011-04-14). "Interacting quantum observables: categorical algebra and diagrammatics". New Journal of Physics. 13 (4): 043016. arXiv: 0906.4725 . Bibcode:2011NJPh...13d3016C. doi:10.1088/1367-2630/13/4/043016. ISSN   1367-2630. S2CID   14259278.
  3. 1 2 Duncan, Ross; Perdrix, Simon (2009). "Graph States and the Necessity of Euler Decomposition". Mathematical Theory and Computational Practice. Lecture Notes in Computer Science. Vol. 5635. Springer Berlin Heidelberg. pp. 167–177. arXiv: 0902.0500 . doi:10.1007/978-3-642-03073-4_18. ISBN   9783642030727.
  4. Backens, Miriam (2014-09-17). "The ZX-calculus is complete for stabilizer quantum mechanics". New Journal of Physics. 16 (9): 093021. arXiv: 1307.7025 . Bibcode:2014NJPh...16i3021B. doi:10.1088/1367-2630/16/9/093021. ISSN   1367-2630. S2CID   27558474.
  5. Backens, Miriam (2015-11-04). "Making the stabilizer ZX-calculus complete for scalars". Electronic Proceedings in Theoretical Computer Science. 195: 17–32. arXiv: 1507.03854 . Bibcode:2015arXiv150703854B. doi:10.4204/eptcs.195.2. ISSN   2075-2180. S2CID   14084597.
  6. de Witt, Christian Schröder; Zamdzhiev, Vladimir (2014-12-28). "The ZX-calculus is incomplete for quantum mechanics". Electronic Proceedings in Theoretical Computer Science. 172: 285–292. arXiv: 1404.3633 . doi:10.4204/EPTCS.172.20. ISSN   2075-2180. S2CID   18968166.
  7. Jeandel, Emmanuel; Perdrix, Simon; Vilmart, Renaud (2018). "A Complete Axiomatisation of the ZX-Calculus for Clifford+T Quantum Mechanics". Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science. New York, New York, USA: ACM Press. pp. 559–568. arXiv: 1705.11151 . doi:10.1145/3209108.3209131. ISBN   9781450355834. S2CID   42195704.
  8. 1 2 Hadzihasanovic, Amar; Ng, Kang Feng; Wang, Quanlong (2018). "Two complete axiomatisations of pure-state qubit quantum computing". Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science. Lics '18. ACM. pp. 502–511. doi:10.1145/3209108.3209128. ISBN   9781450355834. S2CID   195347007 . Retrieved 21 May 2019.
  9. Jeandel, Emmanuel; Perdrix, Simon; Vilmart, Renaud (2018). "Diagrammatic Reasoning beyond Clifford+T Quantum Mechanics". Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science. New York, New York, USA: ACM Press. pp. 569–578. arXiv: 1801.10142 . Bibcode:2018arXiv180110142J. doi:10.1145/3209108.3209139. ISBN   9781450355834. S2CID   118959228.
  10. Coecke, Bob; Kissinger, Aleks (2017). Picturing Quantum Processes. Cambridge: Cambridge University Press. doi:10.1017/9781316219317. ISBN   9781316219317.
  11. Heunen, Chris; Vicary, Jamie (2019). Categories for Quantum Theory. Oxford University Press. doi:10.1093/oso/9780198739623.001.0001. ISBN   9780198739616.
  12. Bravyi, Sergey; Haah, Jeongwan (2012-11-27). "Magic-state distillation with low overhead". Physical Review A. 86 (5): 052329. arXiv: 1209.2426 . Bibcode:2012PhRvA..86e2329B. doi:10.1103/physreva.86.052329. ISSN   1050-2947. S2CID   4399674.
  13. 1 2 3 4 Horsman, Dominic; de Beaudrap, Niel (2017-04-27). "The ZX calculus is a language for surface code lattice surgery". arXiv: 1704.08670v2 [quant-ph].
  14. Backens, Miriam; Perdrix, Simon; Wang, Quanlong (2017-01-01). "A Simplified Stabilizer ZX-calculus". Electronic Proceedings in Theoretical Computer Science. 236: 1–20. arXiv: 1602.04744 . doi: 10.4204/eptcs.236.1 . ISSN   2075-2180.
  15. 1 2 van de Wetering, John; Kissinger, Aleks (2019-04-09). "PyZX: Large Scale Automated Diagrammatic Reasoning". arXiv: 1904.04735v1 [quant-ph].
  16. Duncan, Ross; Perdrix, Simon (2010), "Rewriting Measurement-Based Quantum Computations with Generalised Flow", Automata, Languages and Programming, Springer Berlin Heidelberg, pp. 285–296, CiteSeerX   10.1.1.708.1968 , doi:10.1007/978-3-642-14162-1_24, ISBN   9783642141614, S2CID   34644953
  17. Kissinger, Aleks; van de Wetering, John (2019-04-26). "Universal MBQC with generalised parity-phase interactions and Pauli measurements". Quantum. 3: 134. arXiv: 1704.06504 . Bibcode:2019Quant...3..134K. doi: 10.22331/q-2019-04-26-134 . ISSN   2521-327X.
  18. Horsman, Dominic; de Beaudrap, Niel (2017-04-27). "The ZX calculus is a language for surface code lattice surgery". arXiv: 1704.08670v1 [quant-ph].
  19. Perdrix, Simon; Horsman, Dominic; Duncan, Ross; de Beaudrap, Niel (2019-04-29). "Pauli Fusion: a computational model to realise quantum transformations from ZX terms". arXiv: 1904.12817v1 [quant-ph].
  20. Horsman, Dominic; Zohren, Stefan; Roffe, Joschka; Kissinger, Aleks; Chancellor, Nicholas (2016-11-23). "Graphical Structures for Design and Verification of Quantum Error Correction". arXiv: 1611.08012v3 [quant-ph].
  21. Duncan, Ross; Lucas, Maxime (2014-12-27). "Verifying the Steane code with Quantomatic". Electronic Proceedings in Theoretical Computer Science. 171: 33–49. arXiv: 1306.4532 . doi: 10.4204/eptcs.171.4 . ISSN   2075-2180.
  22. Garvie, Liam; Duncan, Ross (2018-02-27). "Verifying the Smallest Interesting Colour Code with Quantomatic". Electronic Proceedings in Theoretical Computer Science. 266: 147–163. doi: 10.4204/eptcs.266.10 . ISSN   2075-2180.
  23. Fagan, Andrew; Duncan, Ross (2019-01-31). "Optimising Clifford Circuits with Quantomatic". Electronic Proceedings in Theoretical Computer Science. 287: 85–105. arXiv: 1901.10114 . Bibcode:2019arXiv190110114F. doi:10.4204/eptcs.287.5. ISSN   2075-2180. S2CID   53979936.
  24. Kissinger, Aleks; Zamdzhiev, Vladimir (2015), "Quantomatic: A Proof Assistant for Diagrammatic Reasoning", Automated Deduction - CADE-25, Springer International Publishing, pp. 326–336, arXiv: 1503.01034 , Bibcode:2015arXiv150301034K, doi:10.1007/978-3-319-21401-6_22, ISBN   9783319214009, S2CID   13292311
  25. Quick, David; Kissinger, Aleks (2015-05-02). "A first-order logic for string diagrams". arXiv: 1505.00343v1 [math.CT].
  26. Coecke, Bob; Kissinger, Aleks (2010). "The Compositional Structure of Multipartite Quantum Entanglement". Automata, Languages and Programming. Lecture Notes in Computer Science. Vol. 6199. Springer Berlin Heidelberg. pp. 297–308. arXiv: 1002.2540 . Bibcode:2010arXiv1002.2540C. doi:10.1007/978-3-642-14162-1_25. ISBN   9783642141614. S2CID   18928433.
  27. Hadzihasanovic, Amar; Duncan, Ross (2015). "A Diagrammatic Axiomatisation for Qubit Entanglement". 2015 30th Annual ACM/IEEE Symposium on Logic in Computer Science. pp. 573–584. arXiv: 1501.07082 . doi:10.1109/lics.2015.59. ISBN   9781479988754. S2CID   14091451.
  28. Backens, Miriam; Kissinger, Aleks (2019-01-31). "ZH: A Complete Graphical Calculus for Quantum Computations Involving Classical Non-linearity". Electronic Proceedings in Theoretical Computer Science. 287: 23–42. doi: 10.4204/eptcs.287.2 . hdl: 2066/204509 . ISSN   2075-2180.