APPLIED QUANTUM COMPUTING III (QUANTUM BIOLOGY & QUANTUM INFORMATION AND DECOHERENCE). - 2025/6

Module Overview

This module comprises two independent halves, on Quantum Biology (Q Bio) plus Quantum Information and Decoherence (Q Info).

• Quantum biology is the study of how quantum mechanical phenomena, such as quantum superposition, tunnelling, and entanglement, can be exploited by living systems to provide evolutionary and/or biological advantages. This half module will cover a range of biological molecules and processes that may exploit quantum effects, such as magnetoreception, photosynthetic light harvesting, and DNA mutations. The goal of this half module is to develop an understanding of how quantum processes could have an impact in nature and how this knowledge can be further used for applications in health and medical sciences. In addition, using research progress in the field of quantum biology and illustrative examples, this course will help to develop an experimental and theoretical understanding of how quantum processes may play a crucial role in maintaining the non-equilibrium state of the biomolecular systems. Many of the subjects acquired through this half module are likely to be of potential use in the summer project. 


• Quantum Information and Decoherence. Quantum information theory provides the formalism and mathematical framework needed to design and eventually operate quantum computers. By the end of this half module, a successful student should have a thorough understanding of the application of this formalism to information processing. This will cover the use of key quantum resources such as entanglement and other correlations, as well as a detailed analysis of the process of measurement, including a range of error mitigation techniques. Further to this, the student will learn to model and handle noise in quantum protocols by means of the density matrix formalism and the concept of generalised measurement, as well as the role of irreversibility via the use of master equations. These topics are not typically covered in undergraduate physics courses, and they will expand the theoretical background presented in previous modules (states and operators in Hilbert spaces, uncertainty and commutation relations, measurement and the spectral theorem, the Schrödinger Equation, Dirac notation, etc) which will mostly focus on isolated quantum systems. This half module requires understanding of the basic formalism of QM, either as courses taught in undergraduate physics degrees, or to have taken the module Introduction to Quantum Computing. While the mathematics involved is not too advanced, students will need to have a basic understanding of linear algebra and calculus, as well as familiarity with Dirac notation (Bra-Ket notation).

Module provider

Mathematics & Physics

Module Leader

RUBIO JIMÉNEZ Jesús (Maths & Phys)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

None

Module content

Indicative content for the Quantum Biology part:

• The history of quantum biology. We begin with a historical overview, tracing the origins and development of Quantum Biology including some basic classical biology.


• Spin-dependent chemical reactions in biology. The radical pair mechanism is an example of the interaction between electron spins in chemical reactions, and governs how some birds sense magnetic fields. We will examine how spin plays a role in diverse biological processes, and are integral to enzymatic catalysis and signal transduction. Chirality-induced spin selectivity effects.


• Quantum processes. Quantum processes in photosynthetic light-harvesting systems showcase the remarkable efficiency of quantum phenomena in energy transfer. Coherent quantum interactions can take place in biomolecules, such as chromophore-proteins. Quantum tunnelling of protons is important in DNA mutations.


• Quantum technology for biology. Quantum technology can provide enhanced sensing capabilities, and quantum computing can help understand biomolecular reactions, such as in the nitrogenase molecule, which, if we could mimic it industrially would lead to enormous savings in energy and carbon emissions from the agri-chemicals industry.


• Latest research. The latest research will be used to inform content in both the applications and modelling.

• Quantum protocols. Revision of the basic formalism of isolated quantum systems, including the notion of quantum state, the Dirac notation, spin operators, orthonormal bases and the Bloch sphere. Transition to the language and notions employed in quantum information theory, including the idea of quantum protocol (preparation and initialisation, manipulation and operations, measurement and readout).


• Coherence and non-locality in the quantum world: Idea of coherence and entanglement in quantum states and how these play a central role in quantum information processing. Introduction to quantitative measures of coherence, entanglement and distance between states. Illustration of these notions with famous examples such as Bell pairs.


• The density matrix. Introduction to dissipation and noise in quantum protocols using the density matrix formalism. This generalises the notion of quantum state for isolated systems (kets or wave functions). The importance of density matrices will be illustrated by examining how entangled states decohere when they interact with their environment. A range of important derivations and exercises will be covered, including the calculation of purity, traces, reduced density matrices, expectation values, and correlations in mixed states.


• The process of measurement. Introduction to modern measurement theory, including a careful analysis of the notion of positive operator-valued measures, quantum decoherence and uncertainty quantification. State-of-the-art techniques to design efficient quantum measurement protocols, which are central in quantum computing, will also be covered, including modern Bayesian theory.


• Irreversibility and the master equation. Introduction to irreversibility in the quantum world using the formalism of open quantum systems. This will include an introduction to master equations and the solution of simple problems such as the decay of superposition states and its quantification.

Assessment pattern

Alternative Assessment

In cases where an alternative re-assessment to an in-class group presentation is required, the alternative assignment will be an individual report/dissertation (Q Bio).

Assessment Strategy

The assessment strategy is designed to provide you with the opportunity to demonstrate:

• adaptability, collaboration skills resulting in team contributions to group outcomes (Q Bio).


• both individual knowledge and problem-solving abilities (Q Bio and Q Info)

• The Quantum Biology project will take the form of a group assignment, to be presented to class members during the last lecture session plus individual deliverables submitted following the group presentation. The project will evaluate recent research in quantum biology. Students will be assigned a group and choose scientific literature to discuss the limitations of current methods, together with research developments that aim to improve this in the areas of quantum biology. The project addresses Learning Outcomes: 1-3.
  
  
  
  
  • The group part of the project will be in the form of a group presentation. Groups will also produce a peer assessment of each other teams' performance. This Group Part will be evaluated on the clarity of the presentation/reflection, including the group's ability to communicate effectively. The form of the presentation will allow non-verbal contributions (written evidence).
  
  
  • The Individual part of the project will be delivered in the form of: a self-assessment of student's own individual contributions to the presentation (outlining student's specific responsibilities and tasks, highlighting key learning outcomes, challenges encountered, lessons learned, and areas for improvement), an evaluation of student's team-mates' contributions (considering factors such as effort, creativity, problem-solving skills, and collaboration), and evaluation of the deliverables of other Groups (considering conveying of understanding, and credibility). [Marks for peer assessment in both Group and Individual components will count towards the assessor student/team, not the assessed student/team].
  
  
  
  


• The Q Info exam addressing Learning Outcomes: 4-7.

• Formative Feedback and Coaching will be provided that is timely and constructive throughout the project duration to guide project groups in their implementation. (Q Bio)


• A team project Proposal and Plan, will be submitted early in the QBio project for formative assessment, outlining the objectives for each individual (i.e. with different tasks for each member of the team), a scope, methodology, and timeline. [Assessed on the clarity, feasibility, and appropriateness of the methodology, techniques and tools.] (QBio)


• SurreyLearn quizzes (Q Bio)


• As preparation for the exam, tutorials will include examples of exam-style and/or past paper questions, followed later by model solutions. (Q Info)

• Verbal feedback will be given in tutorials. (Q Bio and Q Info)


• In-class questions and discussions in tutorials (Q Bio).


• One-to-one advice in open office hours (Q Bio)

Module aims

• Provide a solid foundation of basic quantum biology knowledge that will facilitate the students' understanding of the biological molecules and biomolecular systems that give rise to the quantum effects (Q Bio).
• Develop critical thinking skills to enhance confidence in students' ability to undertake practical work in their dissertation projects (Q Bio).
• Introduce the concept of density matrix to describe quantum states (pure and mixed) (Q Info)
• Introduce the concept of quantum entanglement as a fundamental feature of the quantum world and explore its role as a key resource in QC (Q Info)
• Provide a solid foundation of modern measurement protocols, including generalised measurements and techniques to reduce processing errors (Q Info)
• Explain the process of decoherence as the central challenge in QC (Q Info)
• Give a general introduction to open quantum systems and master equations (Q Info)

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

• Enhance students' knowledge of quantum processes in nature (Q Bio).


• Develop the critical understanding of quantum biology concepts (Q Bio).


• Improve students' group collaboration and presentation skills (Q Bio).


• An introduction to the theoretical ideas behind concepts such as quantum entanglement and decoherence that are central to quantum computing (Q Info)


• practice in problem solving to develop the cognitive skills (Q Info)

• A combination of interactive lectures backed up with guided study to stimulate uptake of subject knowledge (Q Bio and Q Info)


• tutorial demonstration of solutions to key problems, with practice for students both before and after having attempted them for formative feedback (Q Bio and Q Info)


• tutorials to discuss group presentation assessments and class discussion about limitations and challenges in quantum technology and quantum biology. (Q Bio)


• peer learning and teaching with structured Surrey-Learn hosted discussion boards focussed on the above (Q Info)

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: PHYM074

Other information

The School of Mathematics and Physics is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:

Digital Capabilities: Students are introduced to the quantum concepts and mathematical formalism necessary to be able to understand the digital capabilities of quantum computers. (Q Info)

Resourcefulness and Resilience: By participating in group activities, students have the opportunity to demonstrate resourcefulness and resilience through problem-solving, time management, collaboration, conflict resolution, adaptability, seeking feedback, and reflective practices. These skills are invaluable in navigating challenges, both within group settings and in real-world situations, fostering their personal growth and success (Q Bio). Quantum biology is a very interdisciplinary field, and the group presentations will require students to read, absorb and speak to articles and papers in physics, chemistry and biology (Q Bio). Conversely, by working independently through the questions set in the tutorial sheets and then checking their solutions against the model answers provided, students will develop the confidence and resilience to tackle and solve problems in the subject of quantum entanglement and decoherence as it applies in quantum computing (Q Info).

Employability. The group project will enhance students' employability by providing them with practical experience in collaboration, communication, problem-solving, adaptability, accountability to others, time management, leadership, professionalism, and networking. These skills are transferable to various professional settings and contribute to their readiness for the workforce. (Q Bio).

Sustainability: The Quantum Biology half module encompasses quantum processes in biology, such as those that may be involved in photosynthesis and nitrogen fixation in plants, which can have immense importance for sustainability. (Q Bio)

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.