Michael Nielsen | |
---|---|
Born | Michael Aaron Nielsen January 4, 1974 |
Nationality | Australian, American |
Alma mater | University of New Mexico |
Known for | Quantum Computation and Quantum Information Nielsen's theorem |
Awards | Richard C. Tolman Prize Fellow at Caltech, Fulbright Scholar [1] |
Scientific career | |
Fields | Physics, Computer science |
Institutions | Los Alamos National Laboratory Caltech University of Queensland Perimeter Institute Recurse Center |
Thesis | Quantum Information Theory (1998) |
Doctoral advisor | Carlton M. Caves [2] |
Website | http://michaelnielsen.org |
Michael Aaron Nielsen (born January 4, 1974) is an Australian-American quantum physicist, science writer, and computer programming researcher living in San Francisco. [3]
In 1998, Nielsen received his PhD in physics from the University of New Mexico. In 2004, he was recognized as Australia's "youngest academic" and was awarded a Federation Fellowship at the University of Queensland. [4] During this fellowship, he worked at the Los Alamos National Laboratory, Caltech, and at the Perimeter Institute for Theoretical Physics. [2]
Alongside Isaac Chuang, Nielsen co-authored a popular textbook on quantum computing, [5] which has been cited more than 52,000 times as of July 2023. [6]
In 2007, Nielsen shifted his focus from quantum information and computation to “the development of new tools for scientific collaboration and publication”, [7] including the Polymath project with Timothy Gowers, which aims to facilitate "massively collaborative mathematics." [8] Besides writing books and essays, he has also given talks about open science. [9] He was a member of the Working Group on Open Data in Science at the Open Knowledge Foundation. [10]
Nielsen is a strong advocate for open science and has written extensively on the subject, including in his book Reinventing Discovery , which was favorably reviewed in Nature and named one of the Financial Times' best books of 2011. [11] [12]
In 2015 Nielsen published the online textbook Neural Networks and Deep Learning, and joined the Recurse Center as a Research Fellow for a year. [13] [14] He then joined Y Combinator Research as a Research Fellow from 2016 to 2019. [15]
In 2019, Nielsen collaborated with Andy Matuschak to develop Quantum Computing for the Very Curious, a series of interactive essays explaining quantum computing and quantum mechanics. [16] With Patrick Collison, he researched whether scientific progress is slowing down. [17]
Nielsen resides in San Francisco. [18]
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.
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.
This is a timeline of quantum computing.
Theoretical computer science is a subfield of computer science and mathematics that focuses on the abstract and mathematical foundations of computation.
Quantum Information Science is a field that combines the principles of quantum mechanics with information theory to study the processing, analysis, and transmission of information. It covers both theoretical and experimental aspects of quantum physics, including the limits of what can be achieved with quantum information. The term quantum information theory is sometimes used, but it does not include experimental research and can be confused with a subfield of quantum information science that deals with the processing of quantum information.
A trapped-ion quantum computer is one proposed approach to a large-scale quantum computer. Ions, or charged atomic particles, can be confined and suspended in free space using electromagnetic fields. Qubits are stored in stable electronic states of each ion, and quantum information can be transferred through the collective quantized motion of the ions in a shared trap. Lasers are applied to induce coupling between the qubit states or coupling between the internal qubit states and the external motional states.
Nuclear magnetic resonance quantum computing (NMRQC) is one of the several proposed approaches for constructing a quantum computer, that uses the spin states of nuclei within molecules as qubits. The quantum states are probed through the nuclear magnetic resonances, allowing the system to be implemented as a variation of nuclear magnetic resonance spectroscopy. NMR differs from other implementations of quantum computers in that it uses an ensemble of systems, in this case molecules, rather than a single pure state.
Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional computational spaces through the dynamics of a fixed, non-linear system called a reservoir. After the input signal is fed into the reservoir, which is treated as a "black box," a simple readout mechanism is trained to read the state of the reservoir and map it to the desired output. The first key benefit of this framework is that training is performed only at the readout stage, as the reservoir dynamics are fixed. The second is that the computational power of naturally available systems, both classical and quantum mechanical, can be used to reduce the effective computational cost.
Hartmut Neven is a scientist working in quantum computing, computer vision, robotics and computational neuroscience. He is best known for his work in face and object recognition and his contributions to quantum machine learning. He is currently Vice President of Engineering at Google where he is leading the Quantum Artificial Intelligence Lab which he founded in 2012.
In quantum computing, the threshold theorem states that a quantum computer with a physical error rate below a certain threshold can, through application of quantum error correction schemes, suppress the logical error rate to arbitrarily low levels. This shows that quantum computers can be made fault-tolerant, as an analogue to von Neumann's threshold theorem for classical computation. This result was proven by the groups of Dorit Aharanov and Michael Ben-Or; Emanuel Knill, Raymond Laflamme, and Wojciech Zurek; and Alexei Kitaev independently. These results built on a paper of Peter Shor, which proved a weaker version of the threshold theorem.
Scott Joel Aaronson is an American theoretical computer scientist and Schlumberger Centennial Chair of Computer Science at the University of Texas at Austin. His primary areas of research are computational complexity theory and quantum computing.
A spin model is a mathematical model used in physics primarily to explain magnetism. Spin models may either be classical or quantum mechanical in nature. Spin models have been studied in quantum field theory as examples of integrable models. Spin models are also used in quantum information theory and computability theory in theoretical computer science. The theory of spin models is a far reaching and unifying topic that cuts across many fields.
Isaac L. Chuang is an American electrical engineer and physicist. He leads the quanta research group at the Center for Ultracold Atoms at Massachusetts Institute of Technology (MIT). He received his undergraduate degrees in physics (1990) and electrical engineering (1991) and master's in electrical engineering (1991) at MIT. In 1997 he received his PhD in electrical engineering from Stanford University.
Quantum Computation and Quantum Information is a textbook about quantum information science written by Michael Nielsen and Isaac Chuang, regarded as a standard text on the subject. It is informally known as "Mike and Ike", after the candies of that name. The book assumes minimal prior experience with quantum mechanics and with computer science, aiming instead to be a self-contained introduction to the relevant features of both. The focus of the text is on theory, rather than the experimental implementations of quantum computers, which are discussed more briefly.
In quantum computing, a qubit is a unit of information analogous to a bit in classical computing, but it is affected by quantum mechanical properties such as superposition and entanglement which allow qubits to be in some ways more powerful than classical bits for some tasks. Qubits are used in quantum circuits and quantum algorithms composed of quantum logic gates to solve computational problems, where they are used for input/output and intermediate computations.
Matthew Hastings is an American physicist, currently a Principal Researcher at Microsoft. Previously, he was a professor at Duke University and a research scientist at the Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory. He received his PhD in physics at MIT, in 1997, under Leonid Levitov.
Debbie Leung is a University Research Chair at the Institute for Quantum Computing at the University of Waterloo, where she is also affiliated with the Department of Combinatorics and Optimization. She works in theoretical quantum information processing.
Quantum Theory: Concepts and Methods is a 1993 quantum physics textbook by Israeli physicist Asher Peres. Well-regarded among the physics community, it is known for unconventional choices of topics to include.
Tensor networks or tensor network states are a class of variational wave functions used in the study of many-body quantum systems and fluids. Tensor networks extend one-dimensional matrix product states to higher dimensions while preserving some of their useful mathematical properties.
This glossary of quantum computing is a list of definitions of terms and concepts used in quantum computing, its sub-disciplines, and related fields.
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