This document describes a presentation given by Chi-Kwong Li on quantum operations and completely positive linear maps. It begins with an overview of classical and modern computing concepts before introducing quantum computing concepts. It then provides a mathematical formulation of quantum states and operations based on von Neumann's work. It discusses how quantum states of multiple qubits can be represented using tensor products and the exponential complexity this introduces. Finally, it defines quantum operations as completely positive linear maps and provides conditions for complete positivity, unitarity, and trace preservation.
Quantum Computing 101, Part 1 - Hello Quantum WorldAaronTurner9
This is the first part of a blog series on quantum computing, broadly derived from CERN’s Practical introduction to quantum computing video series, Michael Nielson’s Quantum computing for the determined video series, and the following (widely regarded as definitive) references:
• [Hidary] Quantum Computing: An Applied Approach
• [Nielsen & Chuang] Quantum Computing and Quantum Information [a.k.a. “Mike & Ike”]
• [Yanofsky & Mannucci] Quantum Computing for Computer Scientists
My objective is to keep the mathematics to an absolute minimum (albeit not quite zero), in order to engender an intuitive understanding. You can think it as a quantum computing cheat sheet.
Quantum Computing 101, Part 2 - Hello Entangled WorldAaronTurner9
This is the second part of a blog series on quantum computing, broadly derived from CERN’s Practical introduction to quantum computing video series, Michael Nielson’s Quantum computing for the determined video series, and the following (widely regarded as definitive) references:
• [Hidary] Quantum Computing: An Applied Approach
• [Nielsen & Chuang] Quantum Computing and Quantum Information [a.k.a. “Mike & Ike”]
• [Yanofsky & Mannucci] Quantum Computing for Computer Scientists
My objective is to keep the mathematics to an absolute minimum (albeit not quite zero), in order to engender an intuitive understanding. You can think it as a quantum computing cheat sheet.
Introduction to Quantum Computing & Quantum Information TheoryRahul Mee
Note:This is just presentation created for study purpose.
This comprehensive introduction to the field offers a thorough exposition of quantum computing and the underlying concepts of quantum physics.
Quantum Computing 101, Part 1 - Hello Quantum WorldAaronTurner9
This is the first part of a blog series on quantum computing, broadly derived from CERN’s Practical introduction to quantum computing video series, Michael Nielson’s Quantum computing for the determined video series, and the following (widely regarded as definitive) references:
• [Hidary] Quantum Computing: An Applied Approach
• [Nielsen & Chuang] Quantum Computing and Quantum Information [a.k.a. “Mike & Ike”]
• [Yanofsky & Mannucci] Quantum Computing for Computer Scientists
My objective is to keep the mathematics to an absolute minimum (albeit not quite zero), in order to engender an intuitive understanding. You can think it as a quantum computing cheat sheet.
Quantum Computing 101, Part 2 - Hello Entangled WorldAaronTurner9
This is the second part of a blog series on quantum computing, broadly derived from CERN’s Practical introduction to quantum computing video series, Michael Nielson’s Quantum computing for the determined video series, and the following (widely regarded as definitive) references:
• [Hidary] Quantum Computing: An Applied Approach
• [Nielsen & Chuang] Quantum Computing and Quantum Information [a.k.a. “Mike & Ike”]
• [Yanofsky & Mannucci] Quantum Computing for Computer Scientists
My objective is to keep the mathematics to an absolute minimum (albeit not quite zero), in order to engender an intuitive understanding. You can think it as a quantum computing cheat sheet.
Introduction to Quantum Computing & Quantum Information TheoryRahul Mee
Note:This is just presentation created for study purpose.
This comprehensive introduction to the field offers a thorough exposition of quantum computing and the underlying concepts of quantum physics.
Quantum computing - A Compilation of ConceptsGokul Alex
Excerpts of the Talk Delivered at the 'Bio-Inspired Computing' Workshop conducted by Department of Computational Biology and Bioinformatics, University of Kerala.
In this deck from the HPC User Forum in Tucson, John Martinis from Google presents: Quantum Computing and Quantum Supremacy.
Google recently announced that the company has developed a new 72-Qbit quantum processor called Bristlecone.
"The goal of the Google Quantum AI lab is to build a quantum computer that can be used to solve real-world problems. Our strategy is to explore near-term applications using systems that are forward compatible to a large-scale universal error-corrected quantum computer. In order for a quantum processor to be able to run algorithms beyond the scope of classical simulations, it requires not only a large number of qubits. Crucially, the processor must also have low error rates on readout and logical operations, such as single and two-qubit gates."
Watch the video: https://wp.me/p3RLHQ-ipZ
Learn more: https://research.googleblog.com/2018/03/a-preview-of-bristlecone-googles-new.html
and
htttp://hpcuserforum.com
In this talk I will present real-time spectroscopy and different code to perform this kind of calculations.
This presentation can be download here:
http://www.attaccalite.com/wp-content/uploads/2022/03/RealTime_Lausanne_2022.odp
Quantum computers are incredibly powerful machines that take a new approach to processing information. Built on the principles of quantum mechanics, they exploit complex and fascinating laws of nature that are always there, but usually remain hidden from view. By harnessing such natural behavior, quantum computing can run new types of algorithms to process information more holistically. They may one day lead to revolutionary breakthroughs in materials and drug discovery, the optimization of complex manmade systems, and artificial intelligence. We expect them to open doors that we once thought would remain locked indefinitely. Acquaint yourself with the strange and exciting world of quantum computing.
La présentation introduira les principes de fonctionnement des ordinateurs quantiques, la conception de portes logiques et d'algorithmes quantiques simples puis leur exécution sur une véritable puce quantique optoélectronique de l'université de Bristol. Les premiers ordinateurs quantiques sont donc une réalité. Plusieurs attaques et leurs impacts sur les cryptosystèmes symétriques et asymétriques actuels sont analysés et différentes alternatives sont proposées pour être utilisées dans le futur. Les participants sont encouragés à participer avec leur ordinateur portable pour mettre en pratique les exemples abordés.
Quantum computing - A Compilation of ConceptsGokul Alex
Excerpts of the Talk Delivered at the 'Bio-Inspired Computing' Workshop conducted by Department of Computational Biology and Bioinformatics, University of Kerala.
In this deck from the HPC User Forum in Tucson, John Martinis from Google presents: Quantum Computing and Quantum Supremacy.
Google recently announced that the company has developed a new 72-Qbit quantum processor called Bristlecone.
"The goal of the Google Quantum AI lab is to build a quantum computer that can be used to solve real-world problems. Our strategy is to explore near-term applications using systems that are forward compatible to a large-scale universal error-corrected quantum computer. In order for a quantum processor to be able to run algorithms beyond the scope of classical simulations, it requires not only a large number of qubits. Crucially, the processor must also have low error rates on readout and logical operations, such as single and two-qubit gates."
Watch the video: https://wp.me/p3RLHQ-ipZ
Learn more: https://research.googleblog.com/2018/03/a-preview-of-bristlecone-googles-new.html
and
htttp://hpcuserforum.com
In this talk I will present real-time spectroscopy and different code to perform this kind of calculations.
This presentation can be download here:
http://www.attaccalite.com/wp-content/uploads/2022/03/RealTime_Lausanne_2022.odp
Quantum computers are incredibly powerful machines that take a new approach to processing information. Built on the principles of quantum mechanics, they exploit complex and fascinating laws of nature that are always there, but usually remain hidden from view. By harnessing such natural behavior, quantum computing can run new types of algorithms to process information more holistically. They may one day lead to revolutionary breakthroughs in materials and drug discovery, the optimization of complex manmade systems, and artificial intelligence. We expect them to open doors that we once thought would remain locked indefinitely. Acquaint yourself with the strange and exciting world of quantum computing.
La présentation introduira les principes de fonctionnement des ordinateurs quantiques, la conception de portes logiques et d'algorithmes quantiques simples puis leur exécution sur une véritable puce quantique optoélectronique de l'université de Bristol. Les premiers ordinateurs quantiques sont donc une réalité. Plusieurs attaques et leurs impacts sur les cryptosystèmes symétriques et asymétriques actuels sont analysés et différentes alternatives sont proposées pour être utilisées dans le futur. Les participants sont encouragés à participer avec leur ordinateur portable pour mettre en pratique les exemples abordés.
I will explain why quantum computing is interesting, how it works and what you actually need to build a working quantum computer. I will use the superconducting two-qubit quantum processor I built during my PhD as an example to explain its basic building blocks. I will show how we used this processor to achieve so-called quantum speed-up for a search algorithm that we ran on it. Finally, I will give a short overview of the current state of superconducting quantum computing and Google's recently announced effort to build a working quantum computer in cooperation with one of the leading research groups in this field.
Lecture of Professor Amlan Chakrabarti, University of Calcutta on : Fundamentals of Quantum Computing, presented at the Quantum Conference organized by the Dept. of IT, Govt. of West Bengal, India on 12th October 2018
It is a brief presentation on quantum computation, which is created as I have investigation on guided study with my instructor Professor Sen Yang at CUHK
In the first part, Tonda will give a brief introduction to quantum mechanics illustrated on simple discrete systems much like Feynman has in his famous lectures. We will focus on the concepts of spin and photon polarisation.
In the second part we will, one by one, tackle the basics of quantum computation: qubit, quantum computational operation, universal set of quantum instructions and how they relate to Turing machines.
And finally we will take a look at some of the most famous quantum algorithms and for some of them really look under the hood. Also, we will go through a brief overview of the experiments that have been run over the world in past decade or so.
Mathematics (from Greek μάθημα máthēma, “knowledge, study, learning”) is the study of topics such as quantity (numbers), structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Elevating Tactical DDD Patterns Through Object Calisthenics
Quantum operations and completely positive linear maps
1. Quantum Operations and
Completely Positive Linear Maps
Chi-Kwong Li
Department of Mathematics
The College of William and Mary
Williamsburg, Virginia, USA
Chi-Kwong Li Quantum Operations and Completely Positive Maps
2. Quantum Operations and
Completely Positive Linear Maps
Chi-Kwong Li
Department of Mathematics
The College of William and Mary
Williamsburg, Virginia, USA
Currently visiting GWU and NRL.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
3. Quantum Operations and
Completely Positive Linear Maps
Chi-Kwong Li
Department of Mathematics
The College of William and Mary
Williamsburg, Virginia, USA
Currently visiting GWU and NRL.
Joint work with Yiu-Tung Poon (Iowa State University).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
4. Classical computing
Chi-Kwong Li Quantum Operations and Completely Positive Maps
5. Classical computing
Hardware - Beads and bars.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
6. Classical computing
Hardware - Beads and bars.
Input - Using finger skill to change the states of the device.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
7. Classical computing
Hardware - Beads and bars.
Input - Using finger skill to change the states of the device.
Processor - Mechanical process with algorithms based on elementary
arithmetic rules.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
8. Classical computing
Hardware - Beads and bars.
Input - Using finger skill to change the states of the device.
Processor - Mechanical process with algorithms based on elementary
arithmetic rules.
Output - Beads and bars, then recorded by brush and ink.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
9. Modern Computing
Chi-Kwong Li Quantum Operations and Completely Positive Maps
10. Modern Computing
Hardware - Mechanical/electronic/integrated circuits.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
11. Modern Computing
Hardware - Mechanical/electronic/integrated circuits.
Input - Punch cards, keyboards, scanners, sounds, etc. all converted
to binary bits - (0, 1) sequences.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
12. Modern Computing
Hardware - Mechanical/electronic/integrated circuits.
Input - Punch cards, keyboards, scanners, sounds, etc. all converted
to binary bits - (0, 1) sequences.
Processor - Manipulations of (0, 1) sequences using Boolean logic.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
13. Modern Computing
0∨0=0
0∨1=1
1∨0=1
1∨1=1
Hardware - Mechanical/electronic/integrated circuits.
Input - Punch cards, keyboards, scanners, sounds, etc. all converted
to binary bits - (0, 1) sequences.
Processor - Manipulations of (0, 1) sequences using Boolean logic.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
14. Modern Computing
0∨0=0
0∨1=1
1∨0=1
1∨1=1
Hardware - Mechanical/electronic/integrated circuits.
Input - Punch cards, keyboards, scanners, sounds, etc. all converted
to binary bits - (0, 1) sequences.
Processor - Manipulations of (0, 1) sequences using Boolean logic.
Output - (0, 1) sequences realized as visual images, which can be
viewed or printed.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
15. Quantum computing
Quantum Computing Unit
−→ −→
Optical lattices, NMR
Chi-Kwong Li Quantum Operations and Completely Positive Maps
16. Quantum computing
Quantum Computing Unit
−→ −→
Optical lattices, NMR
Hardware - Super conductor, trapped ions, optical lattices, quantum
dot, MNR, etc.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
17. Quantum computing
Quantum Computing Unit
−→ −→
Optical lattices, NMR
Hardware - Super conductor, trapped ions, optical lattices, quantum
dot, MNR, etc.
Input - Quantum states in a specific form - Quantum bits (Qubits).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
18. Quantum computing
Quantum Computing Unit
−→ −→
Optical lattices, NMR
Hardware - Super conductor, trapped ions, optical lattices, quantum
dot, MNR, etc.
Input - Quantum states in a specific form - Quantum bits (Qubits).
Processor - Provide suitable environment for the quantum system of
qubits to evolve.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
19. Quantum computing
Quantum Computing Unit
−→ −→
Optical lattices, NMR
Hardware - Super conductor, trapped ions, optical lattices, quantum
dot, MNR, etc.
Input - Quantum states in a specific form - Quantum bits (Qubits).
Processor - Provide suitable environment for the quantum system of
qubits to evolve.
Output - Measurement of the resulting quantum states.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
20. Quantum computing
Quantum Computing Unit
−→ −→
Optical lattices, NMR
Hardware - Super conductor, trapped ions, optical lattices, quantum
dot, MNR, etc.
Input - Quantum states in a specific form - Quantum bits (Qubits).
Processor - Provide suitable environment for the quantum system of
qubits to evolve.
Output - Measurement of the resulting quantum states.
All these require the understanding of mathematics, physics,
chemistry, computer sciences, engineering, etc.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
21. Mathematical formulation (by von Neumann)
Suppose a quantum system have
two (discrete) measurable physical
sates, say, up spin and down spin
of a particle represented by
Chi-Kwong Li Quantum Operations and Completely Positive Maps
22. Mathematical formulation (by von Neumann)
Suppose a quantum system have
two (discrete) measurable physical
sates, say, up spin and down spin
of a particle represented by
1 0
|0 = and |1 = .
0 1
Chi-Kwong Li Quantum Operations and Completely Positive Maps
23. Mathematical formulation (by von Neumann)
Suppose a quantum system have
two (discrete) measurable physical
sates, say, up spin and down spin
of a particle represented by
1 0
|0 = and |1 = .
0 1
Before measurement, the vector state may be in superposition state
represented by a complex vector
α
v = |ψ = α|0 + β|1 = ∈ C2 , |α|2 + |β|2 = 1.
β
Chi-Kwong Li Quantum Operations and Completely Positive Maps
24. Mathematical formulation (by von Neumann)
Suppose a quantum system have
two (discrete) measurable physical
sates, say, up spin and down spin
of a particle represented by
1 0
|0 = and |1 = .
0 1
Before measurement, the vector state may be in superposition state
represented by a complex vector
α
v = |ψ = α|0 + β|1 = ∈ C2 , |α|2 + |β|2 = 1.
β
One can apply a quantum operation to a state in superposition.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
25. Mathematical formulation (by von Neumann)
Suppose a quantum system have
two (discrete) measurable physical
sates, say, up spin and down spin
of a particle represented by
1 0
|0 = and |1 = .
0 1
Before measurement, the vector state may be in superposition state
represented by a complex vector
α
v = |ψ = α|0 + β|1 = ∈ C2 , |α|2 + |β|2 = 1.
β
One can apply a quantum operation to a state in superposition.
That is the famous “phenomenon” that one can apply a
transformation to the half alive and half dead Schrödinger cat.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
26. Matrix formulation
It is convenient to represent the quantum state |ψ as a rank one
orthogonal projection:
1 1+z x + iy
Q = |ψ ψ| =
2 x − iy 1−z
with x, y, z ∈ R such that x2 + y 2 + z 2 = 1.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
27. Matrix formulation
It is convenient to represent the quantum state |ψ as a rank one
orthogonal projection:
1 1+z x + iy
Q = |ψ ψ| =
2 x − iy 1−z
with x, y, z ∈ R such that x2 + y 2 + z 2 = 1.
There is a Bloch sphere representation of a qubit
Chi-Kwong Li Quantum Operations and Completely Positive Maps
28. Tensor product and complexity
The state of k qubits is represented as the tensor product of k 2 × 2
matrices
Q1 ⊗ · · · ⊗ Qk .
Chi-Kwong Li Quantum Operations and Completely Positive Maps
29. Tensor product and complexity
The state of k qubits is represented as the tensor product of k 2 × 2
matrices
Q1 ⊗ · · · ⊗ Qk .
Recall that for matrices X = (xij ) and Y (may be of different
sizes),
X ⊗ Y = (xij Y ).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
30. Tensor product and complexity
The state of k qubits is represented as the tensor product of k 2 × 2
matrices
Q1 ⊗ · · · ⊗ Qk .
Recall that for matrices X = (xij ) and Y (may be of different
sizes),
X ⊗ Y = (xij Y ).
General entangled states are represented as 2k × 2k density
matrices, i.e., trace one positive semidefinite matrices.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
31. Tensor product and complexity
The state of k qubits is represented as the tensor product of k 2 × 2
matrices
Q1 ⊗ · · · ⊗ Qk .
Recall that for matrices X = (xij ) and Y (may be of different
sizes),
X ⊗ Y = (xij Y ).
General entangled states are represented as 2k × 2k density
matrices, i.e., trace one positive semidefinite matrices.
For k = 1000, we have 21000 = (210 )100 ≈ 10300 . If a high speed
computer can do 1015 operations per second, to do one operation
on each of the states,
Chi-Kwong Li Quantum Operations and Completely Positive Maps
32. Tensor product and complexity
The state of k qubits is represented as the tensor product of k 2 × 2
matrices
Q1 ⊗ · · · ⊗ Qk .
Recall that for matrices X = (xij ) and Y (may be of different
sizes),
X ⊗ Y = (xij Y ).
General entangled states are represented as 2k × 2k density
matrices, i.e., trace one positive semidefinite matrices.
For k = 1000, we have 21000 = (210 )100 ≈ 10300 . If a high speed
computer can do 1015 operations per second, to do one operation
on each of the states, one needs
1030 /1015 = 1015 seconds > 300, 000 centuries!
Chi-Kwong Li Quantum Operations and Completely Positive Maps
33. Quantum operations
Solving the Schrödinger equation, one sees that quantum operations
(channels) on a closed system are unitary similarity transform on
quatnum states ρ (represented as density matrices), i.e.,
ρ(t) → Ut ρ0 Ut† .
Chi-Kwong Li Quantum Operations and Completely Positive Maps
34. Quantum operations
Solving the Schrödinger equation, one sees that quantum operations
(channels) on a closed system are unitary similarity transform on
quatnum states ρ (represented as density matrices), i.e.,
ρ(t) → Ut ρ0 Ut† .
When the state ρ of principal system interacts (involuntarily) with
the state ρE of the (external) environment, one would trace out the
environment so that
Chi-Kwong Li Quantum Operations and Completely Positive Maps
35. Quantum operations
Solving the Schrödinger equation, one sees that quantum operations
(channels) on a closed system are unitary similarity transform on
quatnum states ρ (represented as density matrices), i.e.,
ρ(t) → Ut ρ0 Ut† .
When the state ρ of principal system interacts (involuntarily) with
the state ρE of the (external) environment, one would trace out the
environment so that
r
ρ(t) → Tr E (Ut (ρ ⊗ ρE )Ut† ) = Fj ρFj†
j=1
Fj† Fj = I.
r
for some m × n matrices F1 , . . . , Fr satisfying j=1
Chi-Kwong Li Quantum Operations and Completely Positive Maps
36. Completely positive linear maps
Let Mn be the set of n × n complex matrices,
Chi-Kwong Li Quantum Operations and Completely Positive Maps
37. Completely positive linear maps
Let Mn be the set of n × n complex matrices,
Hn be the set of n × n complex Hermitian matrices.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
38. Completely positive linear maps
Let Mn be the set of n × n complex matrices,
Hn be the set of n × n complex Hermitian matrices.
A map L : Mn → Mm is completely positive if L admits an operator sum
representation
r
L(A) = Fj AFj† ,
j=1
where F1 , . . . , Fr are m × n complex matrices.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
39. Completely positive linear maps
Let Mn be the set of n × n complex matrices,
Hn be the set of n × n complex Hermitian matrices.
A map L : Mn → Mm is completely positive if L admits an operator sum
representation
r
L(A) = Fj AFj† ,
j=1
where F1 , . . . , Fr are m × n complex matrices.
Fj Fj† = Im ;
r
In addition, L is unital if L(In ) = Im , equivalently, j=1
Chi-Kwong Li Quantum Operations and Completely Positive Maps
40. Completely positive linear maps
Let Mn be the set of n × n complex matrices,
Hn be the set of n × n complex Hermitian matrices.
A map L : Mn → Mm is completely positive if L admits an operator sum
representation
r
L(A) = Fj AFj† ,
j=1
where F1 , . . . , Fr are m × n complex matrices.
Fj Fj† = Im ;
r
In addition, L is unital if L(In ) = Im , equivalently, j=1
Fj† Fj = In .
r
L is trace preserving if Tr A = Tr L(A), equivalently, j=1
Chi-Kwong Li Quantum Operations and Completely Positive Maps
41. General problems
Since every quantum operation / channel is a trace preserving completely
positive linear map, it is interesting to study the following.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
42. General problems
Since every quantum operation / channel is a trace preserving completely
positive linear map, it is interesting to study the following.
Question
Given A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm , is there a (unital/trace
preserving) completely positive linear map satisfying L(Aj ) = Bj for all
j = 1, . . . , k?
Chi-Kwong Li Quantum Operations and Completely Positive Maps
43. General problems
Since every quantum operation / channel is a trace preserving completely
positive linear map, it is interesting to study the following.
Question
Given A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm , is there a (unital/trace
preserving) completely positive linear map satisfying L(Aj ) = Bj for all
j = 1, . . . , k?
It is also interesting to consider the following related problems.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
44. General problems
Since every quantum operation / channel is a trace preserving completely
positive linear map, it is interesting to study the following.
Question
Given A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm , is there a (unital/trace
preserving) completely positive linear map satisfying L(Aj ) = Bj for all
j = 1, . . . , k?
It is also interesting to consider the following related problems.
Understand the duality relation between the trace preserving
completely positive linear maps and the unital preserving completely
positive linear maps.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
45. General problems
Since every quantum operation / channel is a trace preserving completely
positive linear map, it is interesting to study the following.
Question
Given A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm , is there a (unital/trace
preserving) completely positive linear map satisfying L(Aj ) = Bj for all
j = 1, . . . , k?
It is also interesting to consider the following related problems.
Understand the duality relation between the trace preserving
completely positive linear maps and the unital preserving completely
positive linear maps.
Determine / deduce properties of L based on the information of
L(A) for some special matrices A.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
46. Basic results
For A ∈ Hn with eigenvalues λ1 (A) ≥ · · · ≥ λn (A), denote by
λ(A) = (λ1 (A), . . . , λn (A)).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
47. Basic results
For A ∈ Hn with eigenvalues λ1 (A) ≥ · · · ≥ λn (A), denote by
λ(A) = (λ1 (A), . . . , λn (A)).
Definition
For x, y ∈ R1×m , we say that x is majorized by y, denoted by x y, if
the sum of entries of x is the same as that of y, and the sum of the k
largest entries of x is not larger than that of y for k = 1, . . . , k − 1.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
48. Basic results
For A ∈ Hn with eigenvalues λ1 (A) ≥ · · · ≥ λn (A), denote by
λ(A) = (λ1 (A), . . . , λn (A)).
Definition
For x, y ∈ R1×m , we say that x is majorized by y, denoted by x y, if
the sum of entries of x is the same as that of y, and the sum of the k
largest entries of x is not larger than that of y for k = 1, . . . , k − 1.
Example (5, 4, 1) (7, 3, 0), (5, 4, 1) (6, 2, 2), (6, 2, 2) (5, 4, 1).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
49. Basic results
For A ∈ Hn with eigenvalues λ1 (A) ≥ · · · ≥ λn (A), denote by
λ(A) = (λ1 (A), . . . , λn (A)).
Definition
For x, y ∈ R1×m , we say that x is majorized by y, denoted by x y, if
the sum of entries of x is the same as that of y, and the sum of the k
largest entries of x is not larger than that of y for k = 1, . . . , k − 1.
Example (5, 4, 1) (7, 3, 0), (5, 4, 1) (6, 2, 2), (6, 2, 2) (5, 4, 1).
It is known that x y if and only if there is a doubly stochastic matrix
D such that x = yD.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
50. Basic results
For A ∈ Hn with eigenvalues λ1 (A) ≥ · · · ≥ λn (A), denote by
λ(A) = (λ1 (A), . . . , λn (A)).
Definition
For x, y ∈ R1×m , we say that x is majorized by y, denoted by x y, if
the sum of entries of x is the same as that of y, and the sum of the k
largest entries of x is not larger than that of y for k = 1, . . . , k − 1.
Example (5, 4, 1) (7, 3, 0), (5, 4, 1) (6, 2, 2), (6, 2, 2) (5, 4, 1).
It is known that x y if and only if there is a doubly stochastic matrix
D such that x = yD.
Recall that a nonnegative matrix D is row (respectively, column)
stochastic if D have all row (respectively, column) sums equal to one;
Chi-Kwong Li Quantum Operations and Completely Positive Maps
51. Basic results
For A ∈ Hn with eigenvalues λ1 (A) ≥ · · · ≥ λn (A), denote by
λ(A) = (λ1 (A), . . . , λn (A)).
Definition
For x, y ∈ R1×m , we say that x is majorized by y, denoted by x y, if
the sum of entries of x is the same as that of y, and the sum of the k
largest entries of x is not larger than that of y for k = 1, . . . , k − 1.
Example (5, 4, 1) (7, 3, 0), (5, 4, 1) (6, 2, 2), (6, 2, 2) (5, 4, 1).
It is known that x y if and only if there is a doubly stochastic matrix
D such that x = yD.
Recall that a nonnegative matrix D is row (respectively, column)
stochastic if D have all row (respectively, column) sums equal to one;
D is doubly stochastic if all row and column sums equal one.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
52. Theorem
Suppose A ∈ Hn and B ∈ Hm . Let a+ (respectively, a− ) be the sum of
the positive (respectively, negative) eigenvalues of A.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
53. Theorem
Suppose A ∈ Hn and B ∈ Hm . Let a+ (respectively, a− ) be the sum of
the positive (respectively, negative) eigenvalues of A. The following
conditions are equivalent.
There is a trace preserving completely positive linear map
L : Mn → Mm such that L(A) = B.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
54. Theorem
Suppose A ∈ Hn and B ∈ Hm . Let a+ (respectively, a− ) be the sum of
the positive (respectively, negative) eigenvalues of A. The following
conditions are equivalent.
There is a trace preserving completely positive linear map
L : Mn → Mm such that L(A) = B.
λ(B) (a+ , 0, . . . , 0, a− ) in R1×m .
Chi-Kwong Li Quantum Operations and Completely Positive Maps
55. Theorem
Suppose A ∈ Hn and B ∈ Hm . Let a+ (respectively, a− ) be the sum of
the positive (respectively, negative) eigenvalues of A. The following
conditions are equivalent.
There is a trace preserving completely positive linear map
L : Mn → Mm such that L(A) = B.
λ(B) (a+ , 0, . . . , 0, a− ) in R1×m .
There is an n × m row stochastic matrix D with the first k rows all
equal and the last n − k rows all equal such that λ(B) = λ(A)D.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
56. Theorem
Suppose A ∈ Hn and B ∈ Hm . Let a+ (respectively, a− ) be the sum of
the positive (respectively, negative) eigenvalues of A. The following
conditions are equivalent.
There is a trace preserving completely positive linear map
L : Mn → Mm such that L(A) = B.
λ(B) (a+ , 0, . . . , 0, a− ) in R1×m .
There is an n × m row stochastic matrix D with the first k rows all
equal and the last n − k rows all equal such that λ(B) = λ(A)D.
One can use D to construct m × n matrices F1 , . . . , Fr with
r = max(m, n) such that B = j=1 Fj AFj† and j=1 Fj† Fj = In .
r r
Chi-Kwong Li Quantum Operations and Completely Positive Maps
57. Theorem
Suppose A ∈ Hn and B ∈ Hm . Let a+ (respectively, a− ) be the sum of
the positive (respectively, negative) eigenvalues of A. The following
conditions are equivalent.
There is a trace preserving completely positive linear map
L : Mn → Mm such that L(A) = B.
λ(B) (a+ , 0, . . . , 0, a− ) in R1×m .
There is an n × m row stochastic matrix D with the first k rows all
equal and the last n − k rows all equal such that λ(B) = λ(A)D.
One can use D to construct m × n matrices F1 , . . . , Fr with
r = max(m, n) such that B = j=1 Fj AFj† and j=1 Fj† Fj = In .
r r
Remark For density matrices A and B, the condition trivially holds.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
58. Theorem
Let A ∈ Hn and B ∈ Hm . The following conditions are equivalent.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
59. Theorem
Let A ∈ Hn and B ∈ Hm . The following conditions are equivalent.
There is a unital completely positive linear map L such that
L(A) = B.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
60. Theorem
Let A ∈ Hn and B ∈ Hm . The following conditions are equivalent.
There is a unital completely positive linear map L such that
L(A) = B.
λn (A) ≤ λj (B) ≤ λ1 (A) for all j = 1, . . . , m.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
61. Theorem
Let A ∈ Hn and B ∈ Hm . The following conditions are equivalent.
There is a unital completely positive linear map L such that
L(A) = B.
λn (A) ≤ λj (B) ≤ λ1 (A) for all j = 1, . . . , m.
There is an n × m column stochastic matrix D such that
λ(B) = λ(A)D.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
62. Theorem
Let A ∈ Hn and B ∈ Hm . The following conditions are equivalent.
There is a unital completely positive linear map L such that
L(A) = B.
λn (A) ≤ λj (B) ≤ λ1 (A) for all j = 1, . . . , m.
There is an n × m column stochastic matrix D such that
λ(B) = λ(A)D.
Remark The condition may fail even if A and B are density matrices.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
63. Theorem
Let A ∈ Hn and B ∈ Hm . The following conditions are equivalent.
There is a unital completely positive linear map L such that
L(A) = B.
λn (A) ≤ λj (B) ≤ λ1 (A) for all j = 1, . . . , m.
There is an n × m column stochastic matrix D such that
λ(B) = λ(A)D.
Remark The condition may fail even if A and B are density matrices.
Question
Can we deduce this result from the previous one using duality of
completely positive linear map?
Chi-Kwong Li Quantum Operations and Completely Positive Maps
64. Question
Assume there is a unital completely positive map sending A to B, and
also a trace preserving completely positive map sending A to B.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
65. Question
Assume there is a unital completely positive map sending A to B, and
also a trace preserving completely positive map sending A to B. Is there
a unital trace preserving completely positive map sending A to B?
Chi-Kwong Li Quantum Operations and Completely Positive Maps
66. Question
Assume there is a unital completely positive map sending A to B, and
also a trace preserving completely positive map sending A to B. Is there
a unital trace preserving completely positive map sending A to B?
The following example shows that the answer is negative.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
67. Question
Assume there is a unital completely positive map sending A to B, and
also a trace preserving completely positive map sending A to B. Is there
a unital trace preserving completely positive map sending A to B?
The following example shows that the answer is negative.
Example
Suppose A = diag (4, 1, 1, 0) and B = diag (3, 3, 0, 0). Then there is a
trace preserving completely positive map sending A to B, and also a
unital completely positive map sending A to B.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
68. Question
Assume there is a unital completely positive map sending A to B, and
also a trace preserving completely positive map sending A to B. Is there
a unital trace preserving completely positive map sending A to B?
The following example shows that the answer is negative.
Example
Suppose A = diag (4, 1, 1, 0) and B = diag (3, 3, 0, 0). Then there is a
trace preserving completely positive map sending A to B, and also a
unital completely positive map sending A to B. But there is no trace
preserving completely positive linear map sending A1 to B1 if
A1 = A − I4 = diag (3, 0, 0, −1) and B1 = B − I4 = diag (2, 2, −1, −1).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
69. Question
Assume there is a unital completely positive map sending A to B, and
also a trace preserving completely positive map sending A to B. Is there
a unital trace preserving completely positive map sending A to B?
The following example shows that the answer is negative.
Example
Suppose A = diag (4, 1, 1, 0) and B = diag (3, 3, 0, 0). Then there is a
trace preserving completely positive map sending A to B, and also a
unital completely positive map sending A to B. But there is no trace
preserving completely positive linear map sending A1 to B1 if
A1 = A − I4 = diag (3, 0, 0, −1) and B1 = B − I4 = diag (2, 2, −1, −1).
Hence, there is no unital trace preserving completely positive map
sending A to B.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
70. Theorem
Let A, B ∈ Hn . The following conditions are equivalent.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
71. Theorem
Let A, B ∈ Hn . The following conditions are equivalent.
There exists a unital trace preserving completely positive map L
such that L(A) = B.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
72. Theorem
Let A, B ∈ Hn . The following conditions are equivalent.
There exists a unital trace preserving completely positive map L
such that L(A) = B.
For each t ∈ R, there exists a trace preserving completely positive
map L such that L(A − tI) = B − tI.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
73. Theorem
Let A, B ∈ Hn . The following conditions are equivalent.
There exists a unital trace preserving completely positive map L
such that L(A) = B.
For each t ∈ R, there exists a trace preserving completely positive
map L such that L(A − tI) = B − tI.
λ(B) λ(A). i.e., there is a doubly stochastic matrix D such that
λ(B) = λ(A)D.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
74. Theorem
Let A, B ∈ Hn . The following conditions are equivalent.
There exists a unital trace preserving completely positive map L
such that L(A) = B.
For each t ∈ R, there exists a trace preserving completely positive
map L such that L(A − tI) = B − tI.
λ(B) λ(A). i.e., there is a doubly stochastic matrix D such that
λ(B) = λ(A)D.
There is a unitary U ∈ Mn such that U AU † has diagonal entries
λ1 (B), . . . , λn (B).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
75. Theorem
Let A, B ∈ Hn . The following conditions are equivalent.
There exists a unital trace preserving completely positive map L
such that L(A) = B.
For each t ∈ R, there exists a trace preserving completely positive
map L such that L(A − tI) = B − tI.
λ(B) λ(A). i.e., there is a doubly stochastic matrix D such that
λ(B) = λ(A)D.
There is a unitary U ∈ Mn such that U AU † has diagonal entries
λ1 (B), . . . , λn (B).
There exist unitary matrices Uj , 1 ≤ j ≤ n such that
1 n †
B = n j=1 Uj AUj .
Chi-Kwong Li Quantum Operations and Completely Positive Maps
76. Theorem
Let A, B ∈ Hn . The following conditions are equivalent.
There exists a unital trace preserving completely positive map L
such that L(A) = B.
For each t ∈ R, there exists a trace preserving completely positive
map L such that L(A − tI) = B − tI.
λ(B) λ(A). i.e., there is a doubly stochastic matrix D such that
λ(B) = λ(A)D.
There is a unitary U ∈ Mn such that U AU † has diagonal entries
λ1 (B), . . . , λn (B).
There exist unitary matrices Uj , 1 ≤ j ≤ n such that
1 n †
B = n j=1 Uj AUj .
B is in the convex hull of the unitary orbit U(A) of A:
{U AU † : U unitary}.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
77. Results and questions on multiple matrices
Theorem
Suppose A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm are diagonal matrices.
Then there is a unital / trace preserving / unital and trace preserving
completely positive linear maps L such that
L(Aj ) = Bj for j = 1, . . . , k
Chi-Kwong Li Quantum Operations and Completely Positive Maps
78. Results and questions on multiple matrices
Theorem
Suppose A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm are diagonal matrices.
Then there is a unital / trace preserving / unital and trace preserving
completely positive linear maps L such that
L(Aj ) = Bj for j = 1, . . . , k
if and only if there is an n × m column / row / doubly stochastic matrix
D such that d(Bj ) = d(Aj )D for j = 1, . . . , k.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
79. Results and questions on multiple matrices
Theorem
Suppose A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm are diagonal matrices.
Then there is a unital / trace preserving / unital and trace preserving
completely positive linear maps L such that
L(Aj ) = Bj for j = 1, . . . , k
if and only if there is an n × m column / row / doubly stochastic matrix
D such that d(Bj ) = d(Aj )D for j = 1, . . . , k.
Here d(R) is the vector of diagonal entries of the square matrix R.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
80. Results and questions on multiple matrices
Theorem
Suppose A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm are diagonal matrices.
Then there is a unital / trace preserving / unital and trace preserving
completely positive linear maps L such that
L(Aj ) = Bj for j = 1, . . . , k
if and only if there is an n × m column / row / doubly stochastic matrix
D such that d(Bj ) = d(Aj )D for j = 1, . . . , k.
Here d(R) is the vector of diagonal entries of the square matrix R.
Remark Evidently, the result can be applied to commuting families
{A1 , . . . , Ak } and {B1 , . . . , Bk }.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
81. Results and questions on multiple matrices
Theorem
Suppose A1 , . . . , Ak ∈ Mn and B1 , . . . , Bk ∈ Mm are diagonal matrices.
Then there is a unital / trace preserving / unital and trace preserving
completely positive linear maps L such that
L(Aj ) = Bj for j = 1, . . . , k
if and only if there is an n × m column / row / doubly stochastic matrix
D such that d(Bj ) = d(Aj )D for j = 1, . . . , k.
Here d(R) is the vector of diagonal entries of the square matrix R.
Remark Evidently, the result can be applied to commuting families
{A1 , . . . , Ak } and {B1 , . . . , Bk }.
Question What about non-commuting families?
Chi-Kwong Li Quantum Operations and Completely Positive Maps
82. Further research
It would be interesting to study the interpolation problem for
general families {A1 , . . . , Ak } and {B1 , . . . , Bk }.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
83. Further research
It would be interesting to study the interpolation problem for
general families {A1 , . . . , Ak } and {B1 , . . . , Bk }.
It is closely related to dilation theory and the study of spectral
inequalities relating a Hermitian matrix and its principal
submatrices.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
84. Further research
It would be interesting to study the interpolation problem for
general families {A1 , . . . , Ak } and {B1 , . . . , Bk }.
It is closely related to dilation theory and the study of spectral
inequalities relating a Hermitian matrix and its principal
submatrices.
For given A1 , . . . , Ak ∈ Hn , it is interesting to characterize the
compact convex set CPm (A1 , . . . , Ak ) of k-tuples of matrices
k
(B1 , . . . , Bk ) ∈ Hm such that
(B1 , . . . , Bk ) = (L(A1 ), . . . , L(Ak ))
for some completely positive linear map L : Mn → Mm .
Chi-Kwong Li Quantum Operations and Completely Positive Maps
85. Further research
It would be interesting to study the interpolation problem for
general families {A1 , . . . , Ak } and {B1 , . . . , Bk }.
It is closely related to dilation theory and the study of spectral
inequalities relating a Hermitian matrix and its principal
submatrices.
For given A1 , . . . , Ak ∈ Hn , it is interesting to characterize the
compact convex set CPm (A1 , . . . , Ak ) of k-tuples of matrices
k
(B1 , . . . , Bk ) ∈ Hm such that
(B1 , . . . , Bk ) = (L(A1 ), . . . , L(Ak ))
for some completely positive linear map L : Mn → Mm .
The problem is interesting even when k = 1.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
86. Further research
It would be interesting to study the interpolation problem for
general families {A1 , . . . , Ak } and {B1 , . . . , Bk }.
It is closely related to dilation theory and the study of spectral
inequalities relating a Hermitian matrix and its principal
submatrices.
For given A1 , . . . , Ak ∈ Hn , it is interesting to characterize the
compact convex set CPm (A1 , . . . , Ak ) of k-tuples of matrices
k
(B1 , . . . , Bk ) ∈ Hm such that
(B1 , . . . , Bk ) = (L(A1 ), . . . , L(Ak ))
for some completely positive linear map L : Mn → Mm .
The problem is interesting even when k = 1.
It is also interesting to impose restriction on the Karus (Choi) rank
r of the completely positive linear map L(A) = j=1 Fj AFj† .
r
Chi-Kwong Li Quantum Operations and Completely Positive Maps
87. A computaional approach
Derive numerical scheme (using gradient flow, positive semi-definite
programming, etc.) to solve the following:
Given A1 , . . . , Ak ∈ Hn , B1 , . . . , Bk ∈ Hm , determine L such that
Chi-Kwong Li Quantum Operations and Completely Positive Maps
88. A computaional approach
Derive numerical scheme (using gradient flow, positive semi-definite
programming, etc.) to solve the following:
Given A1 , . . . , Ak ∈ Hn , B1 , . . . , Bk ∈ Hm , determine L such that
L(Aj ) = Bj , j = 1, . . . , k,
Chi-Kwong Li Quantum Operations and Completely Positive Maps
89. A computaional approach
Derive numerical scheme (using gradient flow, positive semi-definite
programming, etc.) to solve the following:
Given A1 , . . . , Ak ∈ Hn , B1 , . . . , Bk ∈ Hm , determine L such that
L(Aj ) = Bj , j = 1, . . . , k,
and
[L(Eij )] ≥ 0.
Chi-Kwong Li Quantum Operations and Completely Positive Maps
90. A computaional approach
Derive numerical scheme (using gradient flow, positive semi-definite
programming, etc.) to solve the following:
Given A1 , . . . , Ak ∈ Hn , B1 , . . . , Bk ∈ Hm , determine L such that
L(Aj ) = Bj , j = 1, . . . , k,
and
[L(Eij )] ≥ 0.
We may impose additional conditons such as:
Chi-Kwong Li Quantum Operations and Completely Positive Maps
91. A computaional approach
Derive numerical scheme (using gradient flow, positive semi-definite
programming, etc.) to solve the following:
Given A1 , . . . , Ak ∈ Hn , B1 , . . . , Bk ∈ Hm , determine L such that
L(Aj ) = Bj , j = 1, . . . , k,
and
[L(Eij )] ≥ 0.
We may impose additional conditons such as:
L(In ) = Im (unital).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
92. A computaional approach
Derive numerical scheme (using gradient flow, positive semi-definite
programming, etc.) to solve the following:
Given A1 , . . . , Ak ∈ Hn , B1 , . . . , Bk ∈ Hm , determine L such that
L(Aj ) = Bj , j = 1, . . . , k,
and
[L(Eij )] ≥ 0.
We may impose additional conditons such as:
L(In ) = Im (unital).
Tr L(Eij ) = δij for 1 ≤ i, j ≤ n (trace preserving).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
93. A computaional approach
Derive numerical scheme (using gradient flow, positive semi-definite
programming, etc.) to solve the following:
Given A1 , . . . , Ak ∈ Hn , B1 , . . . , Bk ∈ Hm , determine L such that
L(Aj ) = Bj , j = 1, . . . , k,
and
[L(Eij )] ≥ 0.
We may impose additional conditons such as:
L(In ) = Im (unital).
Tr L(Eij ) = δij for 1 ≤ i, j ≤ n (trace preserving).
The sum of r × r principal submatrix of L: Sr (L) = 0 for a given r
(L has rank less than r).
Chi-Kwong Li Quantum Operations and Completely Positive Maps
94. Any comments and suggestions are welcome!
Chi-Kwong Li Quantum Operations and Completely Positive Maps
95. Any comments and suggestions are welcome!
Thank you for your attention!
Chi-Kwong Li Quantum Operations and Completely Positive Maps