What is QUANTUM ERROR CORRECTION? What does QUANTUM ERROR CORRECTION mean? ERROR CORRECTION definition - ERROR CORRECTION meaning - ERROR CORRECTION explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Quantum error correction is used in quantum computing to protect quantum information from errors due to decoherence and other quantum noise. Quantum error correction is essential if one is to achieve fault-tolerant quantum computation that can deal not only with noise on stored quantum information, but also with faulty quantum gates, faulty quantum preparation, and faulty measurements. Classical error correction employs redundancy. The simplest way is to store the information multiple times, and—if these copies are later found to disagree—just take a majority vote; e.g. Suppose we copy a bit three times. Suppose further that a noisy error corrupts the three-bit state so that one bit is equal to zero but the other two are equal to one. If we assume that noisy errors are independent and occur with some probability p. It is most likely that the error is a single-bit error and the transmitted message is three ones. It is possible that a double-bit error occurs and the transmitted message is equal to three zeros, but this outcome is less likely than the above outcome. Copying quantum information is not possible due to the no-cloning theorem. This theorem seems to present an obstacle to formulating a theory of quantum error correction. But it is possible to spread the information of one qubit onto a highly entangled state of several (physical) qubits. Peter Shor first discovered this method of formulating a quantum error correcting code by storing the information of one qubit onto a highly entangled state of nine qubits. A quantum error correcting code protects quantum information against errors of a limited form. Classical error correcting codes use a syndrome measurement to diagnose which error corrupts an encoded state. We then reverse an error by applying a corrective operation based on the syndrome. Quantum error correction also employs syndrome measurements. We perform a multi-qubit measurement that does not disturb the quantum information in the encoded state but retrieves information about the error. A syndrome measurement can determine whether a qubit has been corrupted, and if so, which one. What is more, the outcome of this operation (the syndrome) tells us not only which physical qubit was affected, but also, in which of several possible ways it was affected. The latter is counter-intuitive at first sight: Since noise is arbitrary, how can the effect of noise be one of only few distinct possibilities? In most codes, the effect is either a bit flip, or a sign (of the phase) flip, or both (corresponding to the Pauli matrices X, Z, and Y). The reason is that the measurement of the syndrome has the projective effect of a quantum measurement. So even if the error due to the noise was arbitrary, it can be expressed as a superposition of basis operations—the error basis (which is here given by the Pauli matrices and the identity). The syndrome measurement "forces" the qubit to "decide" for a certain specific "Pauli error" to "have happened", and the syndrome tells us which, so that we can let the same Pauli operator act again on the corrupted qubit to revert the effect of the error. The syndrome measurement tells us as much as possible about the error that has happened, but nothing at all about the value that is stored in the logical qubit—as otherwise the measurement would destroy any quantum superposition of this logical qubit with other qubits in the quantum computer.
Views: 1179 The Audiopedia
Original post: https://www.gcppodcast.com/post/episode-123-post-quantum-cryptography-with-nick-sullivan-and-adam-langley/ Nick Sullivan, and Adam Langley join Melanie and Mark to provide a pragmatic view on post-quantum cryptography and what it means to research security for the potential of quantum computing. Post-quantum cryptography is about developing algorithms that are resistant to quantum computers in conjunction with “classical” computers. It’s about looking at the full picture of potential threats and planning on how to address them using a diversity of types of mathematics in the research. Adam and Nick help clarify the different terminology and techniques that are applied in the research and give a practical understanding of what to expect from a security perspective.
Views: 1057 Google Cloud Platform
What is INFORMATION THEORY? What does INFORMATION THEORY mean? INFORMATION THEORY meaning. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Information theory studies the quantification, storage, and communication of information. It was originally proposed by Claude E. Shannon in 1948 to find fundamental limits on signal processing and communication operations such as data compression, in a landmark paper entitled "A Mathematical Theory of Communication". Now this theory has found applications in many other areas, including statistical inference, natural language processing, cryptography, neurobiology, the evolution and function of molecular codes, model selection in ecology, thermal physics, quantum computing, linguistics, plagiarism detection, pattern recognition, and anomaly detection. A key measure in information theory is "entropy". Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. For example, identifying the outcome of a fair coin flip (with two equally likely outcomes) provides less information (lower entropy) than specifying the outcome from a roll of a die (with six equally likely outcomes). Some other important measures in information theory are mutual information, channel capacity, error exponents, and relative entropy. Applications of fundamental topics of information theory include lossless data compression (e.g. ZIP files), lossy data compression (e.g. MP3s and JPEGs), and channel coding (e.g. for Digital Subscriber Line (DSL)). The field is at the intersection of mathematics, statistics, computer science, physics, neurobiology, and electrical engineering. Its impact has been crucial to the success of the Voyager missions to deep space, the invention of the compact disc, the feasibility of mobile phones, the development of the Internet, the study of linguistics and of human perception, the understanding of black holes, and numerous other fields. Important sub-fields of information theory include source coding, channel coding, algorithmic complexity theory, algorithmic information theory, information-theoretic security, and measures of information. Information theory studies the transmission, processing, utilization, and extraction of information. Abstractly, information can be thought of as the resolution of uncertainty. In the case of communication of information over a noisy channel, this abstract concept was made concrete in 1948 by Claude Shannon in his paper "A Mathematical Theory of Communication", in which "information" is thought of as a set of possible messages, where the goal is to send these messages over a noisy channel, and then to have the receiver reconstruct the message with low probability of error, in spite of the channel noise. Shannon's main result, the noisy-channel coding theorem showed that, in the limit of many channel uses, the rate of information that is asymptotically achievable is equal to the channel capacity, a quantity dependent merely on the statistics of the channel over which the messages are sent. Information theory is closely associated with a collection of pure and applied disciplines that have been investigated and reduced to engineering practice under a variety of rubrics throughout the world over the past half century or more: adaptive systems, anticipatory systems, artificial intelligence, complex systems, complexity science, cybernetics, informatics, machine learning, along with systems sciences of many descriptions. Information theory is a broad and deep mathematical theory, with equally broad and deep applications, amongst which is the vital field of coding theory. Coding theory is concerned with finding explicit methods, called codes, for increasing the efficiency and reducing the error rate of data communication over noisy channels to near the Channel capacity. These codes can be roughly subdivided into data compression (source coding) and error-correction (channel coding) techniques. In the latter case, it took many years to find the methods Shannon's work proved were possible. A third class of information theory codes are cryptographic algorithms (both codes and ciphers). Concepts, methods and results from coding theory and information theory are widely used in cryptography and cryptanalysis. See the article ban (unit) for a historical application. Information theory is also used in information retrieval, intelligence gathering, gambling, statistics, and even in musical composition.
Views: 3203 The Audiopedia
A talk by Daniel Gottesman at the 4th International Conference on Quantum Error Correction, hosted September 11-15, 2017 by Georgia Tech and the Joint Center for Quantum Information and Computer Science at the University of Maryland.
Views: 184 QuICS
A broad introduction to this field of study Watch the next lesson: https://www.khanacademy.org/computing/computer-science/informationtheory/info-theory/v/language-of-coins-2-8-proto-writing?utm_source=YT&utm_medium=Desc&utm_campaign=computerscience Missed the previous lesson? https://www.khanacademy.org/computing/computer-science/cryptography/random-algorithms-probability/v/fermat-primality-test-prime-adventure-part-10?utm_source=YT&utm_medium=Desc&utm_campaign=computerscience Computer Science on Khan Academy: Learn select topics from computer science - algorithms (how we solve common problems in computer science and measure the efficiency of our solutions), cryptography (how we protect secret information), and information theory (how we encode and compress information). About Khan Academy: Khan Academy is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to Khan Academy’s Computer Science channel: https://www.youtube.com/channel/UC8uHgAVBOy5h1fDsjQghWCw?sub_confirmation=1 Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 152295 Khan Academy Labs
Writing code that is resilient upon errors has always been a pain point in all languages. Exceptions are the politically correct means to signal errors in C++, but many applications still resort to error codes for reasons related to ease of understanding, ease of handling errors locally, and efficiency of generated code. This talk shows how a variety of theoretical and practical artifacts can be combined together to address error codes and exceptions in one wholesome, simple package. The generic type expected＜T＞ can be used for both local (error-code-style) and centralized (exception-style) manners, drawing from the strengths of each. EVENT: CppCon 2018 SPEAKER: Andrei Alexandrescu PERMISSIONS: CppCon Organizer provided Coding Tech with the permission to publish this video.
Views: 2945 Coding Tech
Dr. Virgil Gligor, Professor of Electrical and Computer Engineering, Carnegie Mellon and Cylab, presents "On the Fragiliity of Adversary Definitions in Cryptographic Protocols" on November 6, 2008. Note: Original video was 320x240.
Views: 327 Rutgers University
Fundamentals of Computer Network Security This specialization in intended for IT professionals, computer programmers, managers, IT security professionals who like to move up ladder, who are seeking to develop network system security skills. Through four courses, we will cover the Design and Analyze Secure Networked Systems, Develop Secure Programs with Basic Cryptography and Crypto API, Hacking and Patching Web Applications, Perform Penetration Testing, and Secure Networked Systems with Firewall and IDS, which will prepare you to perform tasks as Cyber Security Engineer, IT Security Analyst, and Cyber Security Analyst. course 2 Basic Cryptography and Programming with Crypto API: About this course: In this MOOC, we will learn the basic concepts and principles of cryptography, apply basic cryptoanalysis to decrypt messages encrypted with mono-alphabetic substitution cipher, and discuss the strongest encryption technique of the one-time-pad and related quantum key distribution systems. We will also learn the efficient symmetric key cryptography algorithms for encrypting data, discuss the DES and AES standards, study the criteria for selecting AES standard, present the block cipher operating modes and discuss how they can prevent and detect the block swapping attacks, and examine how to defend against replay attacks. We will learn the Diffie-Hellman Symmetric Key Exchange Protocol to generate a symmetric key for two parties to communicate over insecure channel. We will learn the modular arithmetic and the Euler Totient Theorem to appreciate the RSA Asymmetric Crypto Algorithm, and use OpenSSL utility to realize the basic operations of RSA Crypto Algorithm. Armed with these knowledge, we learn how to use PHP Crypto API to write secure programs for encrypting and decrypting documents and for signing and verify documents. We then apply these techniques to enhance the registration process of a web site which ensures the account created is actually requested by the owner of the email account. Module 2 - Symmetric Key Cryptography In this module we present the basic mechanism of symmetric key crytography algorithms, discuss the DES and AES standard, describe the criteria for selecting AES standard, present the block cipher operating modes and discuss how the block swapping attacks and replay attacks can be prevented and detected. Learning Objectives • Understand the criteria for selecting crypto algorithms • Perform cryptoanalysis on simple ciphers • Select operating modes for symmetric encryption and to prevent block swapping and replay attacks • Understand DES and AES standards and their buildig blocks Subscribe at: https://www.coursera.org
Views: 345 intrigano
Start your FREE Trial of The Great Courses Plus and watch the course here: https://www.thegreatcoursesplus.com/special-offer?utm_source=US_OnlineVideo&utm_medium=SocialMediaEditorialYouTube&utm_campaign=145596 The science of information is the most influential, yet perhaps least appreciated field in science today. Never before in history have we been able to acquire, record, communicate, and use information in so many different forms. Never before have we had access to such vast quantities of data of every kind. This revolution goes far beyond the limitless content that fills our lives, because information also underlies our understanding of ourselves, the natural world, and the universe. It is the key that unites fields as different as linguistics, cryptography, neuroscience, genetics, economics, and quantum mechanics. And the fact that information bears no necessary connection to meaning makes it a profound puzzle that people with a passion for philosophy have pondered for centuries. Little wonder that an entirely new science has arisen that is devoted to deepening our understanding of information and our ability to use it. Called information theory, this field has been responsible for path-breaking insights such as the following: What is information? In 1948, mathematician Claude Shannon boldly captured the essence of information with a definition that doesn’t invoke abstract concepts such as meaning or knowledge. In Shannon’s revolutionary view, information is simply the ability to distinguish reliably among possible alternatives. The bit: Atomic theory has the atom. Information theory has the bit: the basic unit of information. Proposed by Shannon’s colleague at Bell Labs, John Tukey, bit stands for “binary digit”—0 or 1 in binary notation, which can be implemented with a simple on/off switch. Everything from books to black holes can be measured in bits. Redundancy: Redundancy in information may seem like mere inefficiency, but it is a crucial feature of information of all types, including languages and DNA, since it provides built-in error correction for mistakes and noise. Redundancy is also the key to breaking secret codes. Building on these and other fundamental principles, information theory spawned the digital revolution of today, just as the discoveries of Galileo and Newton laid the foundation for the scientific revolution four centuries ago. Technologies for computing, telecommunication, and encryption are now common, and it’s easy to forget that these powerful technologies and techniques had their own Galileos and Newtons. The Science of Information: From Language to Black Holes covers the exciting concepts, history, and applications of information theory in 24 challenging and eye-opening half-hour lectures taught by Professor Benjamin Schumacher of Kenyon College. A prominent physicist and award-winning educator at one of the nation’s top liberal arts colleges, Professor Schumacher is also a pioneer in the field of quantum information, which is the latest exciting development in this dynamic scientific field. Start your FREE Trial of The Great Courses Plus and watch the course here: https://www.thegreatcoursesplus.com/special-offer?utm_source=US_OnlineVideo&utm_medium=SocialMediaEditorialYouTube&utm_campaign=145596 Don’t forget to subscribe to our channel – we are adding new videos all the time! https://www.youtube.com/subscription_center?add_user=TheGreatCourses
Views: 2092 The Great Courses Plus
Quantum Information Science - An Overview. We are starting with a series of lectures on Quantum Information Science. Each lecture will contain 4 parts (an introduction to the subject, key concepts, we will explain how it works and at the end we will do some practical example). So welcome to the first video in Quantum Information Science series of lectures and tutorials. Today's topic will be an overview of Quantum Information Science topic. The first part will be the introduction. We will start with the introduction to Quantum Information Science by explaining what Quantum Information Science actually is, tell you few main definitions and present the chapters we are going to cover until the end of the video. So Quantum Information Science is the area of study where information is affected, generated and processed by quantum behavior. The second part will be the key concepts. We will mention and explain all fundamental terms and concepts which are going to be covered in their own lecture, later in Quantum Information Science playlist. For Quantum Information Science, key terms are: -quantum computing -quantum algorithms -Quantum complexity theory -Quantum cryptography -Quantum error correction -Quantum information theory -Quantum entanglement Then we will give a real-world example on how the concept works including illustrations and explanation. For example, we will explain, animate and illustrate how quantum cryptography works indeed. And at the end we will do some hands-on project (coding or math background) so you could get a practical meaning for the specific topic. For example, we will write and explain in details theoretical computer science behind quantum complexity theory. That would be all for now. See you soon with the next lecture. Please make sure you subscribe (click on that bell icon, so you could get notifications when we release new video), like and comment on the video in case you want to share your thoughts or ask any questions. You can visit our official website: www.stemiac.com, where you will find the entire article about this topic, forum where you can ask and answer questions and be a part of our growing community. You can also find the entire source code for any given topic, all video lectures and many more! #QuantumInformationScience #QuantumScience #QuantumInformation
Views: 4 Stemiac
What is Information? - Part 2a - Introduction to Information Theory: Script: http://crackingthenutshell.org/what-is-information-part-2a-information-theory ** Please support my channel by becoming a patron: http://www.patreon.com/crackingthenutshell ** Or... how about a Paypal Donation? http://crackingthenutshell.org/donate Thanks so much for your support! :-) - Claude Shannon - Bell Labs - Father of Information Theory - A Mathematical Theory of Communication - 1948 - Book, co-written with Warren Weaver - How to transmit information efficiently, reliably & securely through a given channel (e.g. tackling evesdropping) - Applications. Lossless data compression (ZIP files). Lossy data compression (MP3, JPG). Cryptography, thermal physics, quantum computing, neurobiology - Shannon's definition not related to meaningfulness, value or other qualitative properties - theory tackles practical issues - Shannon's information, a purely quantitative measure of communication exchanges - Shannon's Entropy. John von Neumann. Shannon's information, information entropy - avoid confusion with with thermodynamical entropy - Shannon's Entropy formula. H as the negative of a certain sum involving probabilities - Examples: fair coin & two-headed coin - Information gain = uncertainty reduction in the receiver's knowledge - Shannon's entropy as missing information, lack of information - Estimating the entropy per character of the written English language - Constraints such as "I before E except after C" reduce H per symbol - Taking into account redundancy & contextuality - Redundancy, predictability, entropy per character, compressibility - What is data compression? - Extracting redundancy - Source Coding Theorem. Entropy as a lower limit for lossless data compression. - ASCII codes - Example using Huffman code. David Huffman. Variable length coding - Other compression techniques: arithmetic coding - Quality vs Quantity of information - John Tukey's bit vs Shannon's bit - Difference between storage bit & information content. Encoded data vs Shannon's information - Coming in the next video: error correction and detection, Noisy-channel coding theorem, error-correcting codes, Hamming codes, James Gates discovery, the laws of physics, How does Nature store Information, biology, DNA, cosmological & biological evolution
Views: 56640 Cracking The Nutshell
One of the strangest features of quantum mechanics is also potentially its most useful: entanglement. By harnessing the ability for two particles to be intimately intertwined across great distances, researchers are working to create technologies that even Einstein could not imagine, from quantum computers that can run millions of calculations in parallel, to new forms of cryptography that may be impossible to crack. Join us as we explore the coming age of quantum technology, which promises to bring with it a far deeper understanding of fundamental physics. PARTICIPANTS: Jerry Chow, Julia Kempe, Seth Lloyd, Kathy-Anne Soderberg MODERATOR: George Musser Original program date: JUNE 3, 2017 FIND OUT MORE ABOUT THE PROGRAM AND PARTICIPANTS: https://www.worldsciencefestival.com/programs/the-qubit-revolution/ This program is part of the Big Ideas Series, made possible with support from the John Templeton Foundation. SUBSCRIBE to our YouTube Channel for all the latest from WSF VISIT our Website: http://www.worldsciencefestival.com/ LIKE us on Facebook: https://www.facebook.com/worldscience... FOLLOW us on Twitter: https://twitter.com/WorldSciFest Introduction of Participants 00:25 Program Begins: Quantum mechanics, weird or unfamiliar? 01:38 How much power is 20 Qubit's? 10:28 What are the pros and cons of Superconducting quantum computing? 25:55 The factorization problem 40:01 Is there a relationship between quantum computing and machine learning? 48:31 Q & A 54:17 This program was filmed live at the 2017 World Science Festival and edited for YouTube.
Views: 43051 World Science Festival
Google Tech Talks November, 15 2007 ABSTRACT Neurocomputational models provide fundamental insights towards understanding the human brain circuits for learning new associations and organizing our world into appropriate categories. In this talk I will review the information-processing functions of four interacting brain systems for learning and categorization: (1) the basal ganglia which incrementally adjusts choice behaviors using environmental feedback about the consequences of our actions, (2) the hippocampus which supports learning in other brain regions through the creation of new stimulus representations (and, hence, new similarity relationships) that reflect important statistical regularities in the environment, (3) the medial septum which works in a feedback-loop with the hippocampus, using novelty-detection to alter the rate at which stimulus representations are updated through experience, (4) the frontal lobes which provide for selective attention and executive control of learning and memory. The computational models to be described have been evaluated through a variety of empirical methodoligies including human functional brain imaging, studies of patients with localized brain damage due to injury or early-stage neurodegenerative diseases, behavioral genetic studies of naturally-occuring individual variability, as well as comparative lesion and genetic studies with rodents. Our applications of these models to engineering and computer science including automated anomaly detection systems for mechanical fault diagnosis on US Navy helicopters and submarines as well more recent contributions to the DoD's DARPA program for Biologically Inspired Cognitive Architectures (BICA). Speaker: Dr. Mark Gluck Mark Gluck is a Professor of Neuroscience at Rutgers University - Newark, co-director of the Rutgers Memory Disorders Project, and publisher of the public health newsletter, Memory Loss and the Brain. He works at the interface between neuroscience, psychology, and computer science, where his research focuses on the neural bases of learning and memory, and the consequences of memory loss due to aging, trauma, and disease. He is the co-author of "Gateway to Memory: An Introduction to Neural Network Models of the Hippocampus and Memory " (MIT Press, 2001) and a forthcoming undergraduate textbook, "Learning and Memory: From Brain to Behavior." He has edited several other books and has published over 60 scientific journal articles. His awards include the Distinguished Scientific Award for Early Career Contributions from the American Psychological Society and the Young Investigator Award for Cognitive and Neural Sciences from the Office of Naval Research. In 1996, he was awarded a NSF Presidential Early Career Award for Scientists and Engineers by President Bill Clinton. For more information, see http://www.gluck.edu.
Views: 60245 GoogleTechTalks
Panel Discussion with leading Quantum computing technology experts exploring its future: challenges, applications, potential benefits, and threats. Panel participants Andrew Lord, Head of Optics at BT Kelly Richdale, VP Quantum Safe Security at ID Quantique Prof. Keith Martin, Information Security, Royal Holloway, UoL Richard Murray, Lead Technologist at Innovate UK Shadi Razak, CTO at CyNation Quantum technology is a technical reality and not a science fiction, and its certain uses are already revenue generating. £270m government investment into quantum computing technologies in 2013 was a great move, however, more must be invested if UK wants to further fuel its ambition of becoming a global leader and pioneer the industry. The ethical issues are going to be particularly important. The capability of a quantum computer to undermine most public-key cryptography (PKC) in use today, presents a serious challenge to society and, arguably, could prevent the technology from further commercialisation. Having said that, other technologies such as Artificial Intelligence are also contributing to this ethical challenge for economy and society. The ability to break PKC drives a massive research initiative to build new public key encryption algorithms and other cryptographic tools to safeguard data in a quantum computing world. However, another broadly used symmetric type of cryptography is quantum safe already and will be refined even further. Developing quantum algorithms will help financial sectors to conduct highly accurate financial modelling as well as predict future events in trading. A quantum computer can process a vast number of calculations simultaneously, analyse very complex variables, and build precise predictive models from complex data. This can be applied in weather forecasting, traffic management or route planning, to name a few. The issue of cybersecurity in the quantum age is manifold and strongly associated with the vulnerability of public key cryptography in use today in most infrastructures and systems. On the one hand, we do not know how much time it will take two or three major players to dominate the market and potentially break them; or whether it is going to happen at all – currently there is no a universal quantum computer having this capability. On the other hand, quantum-enabled security itself will offer 100% bullet-proof protection guaranteed by the laws of physics. Quantum enabled algorithms will enable organisations to rapidly detect infinite number of manifestations of malicious behaviours and fraud scenarios, making an attack non-viable. A powerful enough quantum computer to threaten cryptographic standards, will be put under lots of control and its owner may well face strong headwinds to get export clearance for its technology. However, since we do not have a “United Nations” of Cybersecurity or a single global regulator, we need to look very seriously at how to avoid the risk for public safety, and make sure the world is secure before quantum computers are unleashed. The other use cases of quantum we look forward to see in the future: • Quantum Artificial Intelligence application in scientific discovery, biotech and biological systems modelling; • Quantum simulation to accelerate the design of quantum electronic devices beyond the reach of supercomputers; • Quantum chemistry to design drugs in the form of small molecules to fight cancer; • Quantum gravity sensing devices to precisely analyse underground infrastructure and its composition; • Quantum glasses for the blind to recreate the surrounding environment within a certain distance. • Quantum PUF (physical unclonable function) to prevent counterfeit drugs; Stay tuned as more uses are coming! One will not have to be a quantum physicist to use them.
Views: 103 CyNation
This talk discards hand-wavy pop-science metaphors and answers a simple question: from a computer science perspective, how can a quantum computer outperform a classical computer? Attendees will learn the following: - Representing computation with basic linear algebra (matrices and vectors) - The computational workings of qbits, superposition, and quantum logic gates - Solving the Deutsch oracle problem: the simplest problem where a quantum computer outperforms classical methods - Bonus topics: quantum entanglement and teleportation The talk concludes with a live demonstration of quantum entanglement on a real-world quantum computer, and a demo of the Deutsch oracle problem implemented in Q# with the Microsoft Quantum Development Kit. This talk assumes no prerequisite knowledge, although comfort with basic linear algebra (matrices, vectors, matrix multiplication) will ease understanding. See more at https://www.microsoft.com/en-us/research/video/quantum-computing-computer-scientists/
Views: 172666 Microsoft Research
Hamming Code Simply Explained ( Tutorial Video ) Calculating the Hamming Code: The key to the Hamming Code is the use of extra parity bits to allow the identification of a single error. Create the code word as follows: 1. Mark all bit positions that are powers of two as parity bits. (positions 1, 2, 4, 8, 16, 32, 64, etc.) 2. All other bit positions are for the data to be encoded. (positions 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 17, etc.) 3. Each parity bit calculates the parity for some of the bits in the code word. The position of the parity bit determines the sequence of bits that it alternately checks and skips. Position 1: check 1 bit, skip 1 bit, check 1 bit, skip 1 bit, etc. (1,3,5,7,9,11,13,15,...) Position 2: check 2 bits, skip 2 bits, check 2 bits, skip 2 bits, etc. (2,3,6,7,10,11,14,15,...) Position 4: check 4 bits, skip 4 bits, check 4 bits, skip 4 bits, etc. (4,5,6,7,12,13,14,15,20,21,22,23,...) Position 8: check 8 bits, skip 8 bits, check 8 bits, skip 8 bits, etc. (8-15,24-31,40-47,...) Position 16: check 16 bits, skip 16 bits, check 16 bits, skip 16 bits, etc. (16-31,48-63,80-95,...) Position 32: check 32 bits, skip 32 bits, check 32 bits, skip 32 bits, etc. (32-63,96-127,160-191,...) etc. 4. Set a parity bit to 1 if the total number of ones in the positions it checks is odd. Set a parity bit to 0 if the total number of ones in the positions it checks is even. Simple method , easy method , animation , calculate
Views: 202615 Jithesh Kunissery
WW2 Encryption is explored with a focus on the Enigma. Read more here. Watch the next lesson: https://www.khanacademy.org/computing/computer-science/cryptography/crypt/v/perfect-secrecy?utm_source=YT&utm_medium=Desc&utm_campaign=computerscience Missed the previous lesson? https://www.khanacademy.org/computing/computer-science/cryptography/crypt/v/frequency-stability?utm_source=YT&utm_medium=Desc&utm_campaign=computerscience Computer Science on Khan Academy: Learn select topics from computer science - algorithms (how we solve common problems in computer science and measure the efficiency of our solutions), cryptography (how we protect secret information), and information theory (how we encode and compress information). About Khan Academy: Khan Academy is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to Khan Academy’s Computer Science channel: https://www.youtube.com/channel/UC8uHgAVBOy5h1fDsjQghWCw?sub_confirmation=1 Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 189809 Khan Academy Labs
A Google TechTalk, 2018-12-05, presented by Alessandro Barenghi ABSTRACT: This talk will present LEDAkem and LEDApkc, a key agreement scheme and a public key encryption scheme resistant against attacks with both classical and quantum computers. In this talk I will present the schemes and report recent results on how we can automatically generate key sizes and cryptosystem parameters tailored for a desired security level, providing practical performance figures. About the speaker: Alessandro Barenghi is currently assistant professor at Politecnico di Milano, and one of the proposers of the LEDAkem/LEDApkc cryptoschemes to the NIST post-quantum standardization initiative.
Views: 1091 GoogleTechTalks
QIP 2016, Banff, 10-16 January 2016 Date: 12 Jan 2016 Title: "Holographic quantum error- correcting codes: toy models for the bulk/boundary correspondence" Authors: Fernando Pastawski, Beni Yoshida, Daniel Harlow and John Preskill. We propose a novel tensor network construction of quantum error-correcting codes inspired by properties of the celebrated holographic correspondence. Our building block is a special family of tensors with multiple indices of equal dimension and admitting a unitary interpretation for any balanced index bipartition. By properly identifying uncontracted indices as input or output, the entire tensor network can be interpreted as an isometry, an encoding map for a quantum error-correcting code. The resulting isometry captures key features of the holographic (bulk/boundary) correspondence. In particular, we provide a systematic procedure for representing logical operators on specific subsets of physical qubits which we call the greedy reconstruction algorithm. This procedure, mimics the Rindler-wedge reconstruction present in holography and explicitly realizes the connection with quantum codes proposed by Almheiri et al.. Furthermore, by interpreting the graph structure of a tensor network as a discrete geometry, we make contact with a holographic statement due to Ryu and Takayanagi relating entanglement with minimal surfaces. Namely, under simple graph theoretic assumptions, we prove a max-flow/min-cut statement by which the entanglement of a sub-region is equal to the minimal number of cuts needed to disconnect the region from its complement. The proposed framework provides a flexible way to design novel quantum codes, allows explicitly realizing tailored entanglement structures. http://arxiv.org/abs/1503.06237
Views: 97 Iqst Ucalgary
The field of computer science summarised. Learn more at this video's sponsor https://brilliant.org/dos Computer science is the subject that studies what computers can do and investigates the best ways you can solve the problems of the world with them. It is a huge field overlapping pure mathematics, engineering and many other scientific disciplines. In this video I summarise as much of the subject as I can and show how the areas are related to each other. You can buy this poster here: North America: https://store.dftba.com/products/map-of-computer-science-poster Everywhere else: https://www.redbubble.com/people/dominicwalliman/works/27929629-map-of-computer-science?p=poster&finish=semi_gloss&size=small Get all my other posters here: https://www.redbubble.com/people/dominicwalliman A couple of notes on this video: 1. Some people have commented that I should have included computer security alongside hacking, and I completely agree, that was an oversight on my part. Apologies to all the computer security professionals, and thanks for all the hard work! 2. I also failed to mention interpreters alongside compilers in the complier section. Again, I’m kicking myself because of course this is an important concept for people to hear about. Also the layers of languages being compiled to other languages is overly convoluted, in practice it is more simple than this. I guess I should have picked one simple example. 3. NP-complete problems are possible to solve, they just become very difficult to solve very quickly as they get bigger. When I said NP-complete and then "impossible to solve", I meant that the large NP-complete problems that industry is interested in solving were thought to be practically impossible to solve. And free downloadable versions of this and the other posters here. If you want to print them out for educational purposes please do! https://www.flickr.com/photos/[email protected]/ Thanks so much to my supporters on Patreon. If you enjoy my videos and would like to help me make more this is the best way and I appreciate it very much. https://www.patreon.com/domainofscience I also write a series of children’s science books call Professor Astro Cat, these links are to the publisher, but they are available in all good bookshops around the world in 18 languages and counting: Frontiers of Space (age 7+): http://nobrow.net/shop/professor-astro-cats-frontiers-of-space/ Atomic Adventure (age 7+): http://nobrow.net/shop/professor-astro-cats-atomic-adventure/ Intergalactic Activity Book (age 7+): http://nobrow.net/shop/professor-astro-cats-intergalactic-activity-book/ Solar System Book (age 3+, available in UK now, and rest of world in spring 2018): http://nobrow.net/shop/professor-astro-cats-solar-system/? Solar System App: http://www.minilabstudios.com/apps/professor-astro-cats-solar-system/ And the new Professor Astro Cat App: https://itunes.apple.com/us/app/galactic-genius-with-astro-cat/id1212841840?mt=8 Find me on twitter, Instagram, and my website: http://dominicwalliman.com https://twitter.com/DominicWalliman https://www.instagram.com/dominicwalliman https://www.facebook.com/dominicwalliman
Views: 1629561 Domain of Science
Daniel Lidar visited the Quantum AI Lab at Google LA to give a talk: "Quantum Information Processing: Are We There Yet?" This talk took place on January 22, 2015. Abstract: Quantum information processing holds great promise, yet large-scale, general purpose quantum computers capable of solving hard problems are not yet available despite 20+ years of immense effort. In this talk I will describe some of this promise and effort, as well as the obstacles and ideas for overcoming them using error correction techniques. I will focus on a special purpose quantum information processor called a quantum annealer, designed to speed up the solution to tough optimization problems. In October 2011 USC and Lockheed-Martin jointly founded a quantum computing center housing a commercial quantum annealer built by the Canadian company D-Wave Systems. A similar device is operated by NASA and Google. These processors use superconducting flux qubits to minimize the energy of classical spin-glass models with as many spins as qubits, an NP-hard problem with numerous applications. There has been much controversy surrounding the D-Wave processors, questioning whether they offer any advantage over classical computing. I will survey the recent work we have done to benchmark the processors against highly optimized classical algorithms, to test for quantum effects, and to perform error correction. Bio: Daniel Lidar has worked in quantum computing for nearly 20 years. He is a professor of electrical engineering, chemistry, and physics at USC, and hold a Ph.D. in physics from the Hebrew University of Jerusalem. His work revolves around various aspects of quantum information science, including quantum algorithms, quantum control, the theory of open quantum systems, and theoretical as well as experimental adiabatic quantum computation. He is a Fellow of the AAAS, APS, and IEEE. Lidar is the Director of the USC Center for Quantum Information Science and Technology, and is the Scientific Director of the USC-Lockheed Martin Center for Quantum Computing. Two of his former graduate students are now research scientists at Google’s quantum artificial intelligence lab.
Views: 13795 GoogleTechTalks
What is a quantum computer and what is quantum computing? Click to subscribe! ► http://bit.ly/Scopes_Sub ◄ Full agenda below! https://eestalktech.com/what-is-quantum-computing Twitter: @Keysight_Daniel https://twitter.com/Keysight_Daniel Learn more about using oscilloscopes: http://oscilloscopelearningcenter.com Check out the EEs Talk Tech electrical engineering podcast: https://eestalktech.com The 2-Minute Guru Season 2 playlist: https://www.youtube.com/playlist?list=PLzHyxysSubUlqBguuVZCeNn47GSK8rcso More about Keysight oscilloscopes: http://bit.ly/SCOPES Check out our blog: http://bit.ly/ScopesBlog Agenda: 0:45 Intro Lee Barford's job is to help to guide Keysight into the quantum computing industry and enable quantum computing experts 2:00 Why is quantum computing/a quantum computer important? Clock rates for digital processors stopped getting faster around 2006 because of excessive heat The processor manufacturers realized they needed more processor parallelism Graphics processor units (GPUs) can be used as vector and matrix computational machines Bitcoin utilizes this method. 6:00 What does the development of quantum computing and quantum computers mean for the future? Gates being made with feature size of the digital transistor that have an effective gate length of down to 7 nm Now we're pushing below 5 nm, and there are not many unit cells of silicon left in the layer. (one unit cell of silicon is 0.5 nanometer) The Heisenberg uncertainty principle comes into play at this point because there are few enough atoms that quantum mechanical effects will disturb electronics. These quantum mechanical effects include a superposition of states (Schrodinger's cat) and low error tolerance. 10:20 When will Moore's law fail? Quantum computing and quantum computers are one way of moving the computing industry past this barrier by taking advantage of quantum effects - engineering with them - to build a quantum computer that will do certain tasks much faster than today's computers. 15:20 Questions for future episodes: What sort of technology does it take to make a quantum computer? Where are current experiments probing? Why are people funding quantum computing research and the building of quantum computers? What problems are quantum computing (and quantum computers) working to solve? 17:30 Using quantum effects Quantum computers probably won't be used in consumer devices because it currently requires a very low temperature and/or a vacuum. 18:00 The quantum computer's fundamental storage unit is a qubit (quantum bit). It can be in states 1 or 0 with some finite probability 19:00 You can set up a quantum register to store multiple potential qubits, and when read out, have an identical probability to be either of these numbers. A quantum register can store multiple states at once, but only one register value can be read out of the quantum register. 21:00 How do you get the desired value out of a quantum register? You do as much of the computation ahead of time and then read the quantum computers quantum register. It works because the answer is either such a high probability to be correct that you don't need to check it, or it is very easy to double check if the answer is correct. 21:00 How do you get the desired value out of a quantum register? You do as much of the computation ahead of time and then read the quantum computers quantum register. 22:30 Quantum computers are good at factoring very large numbers (breaking RSA in cryptography) #oscilloscope #oscilloscopes #electronics #electricalengineering
Views: 1724 Keysight Labs
Quantum Information (PSI 13/14, Review, PHYS 635) - Andrew Childs (University of Maryland) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbOSAZy4zsHlO2Az61tnb_gQ Lecture 1 Qubits, unitary operations and quantum protocols (superdense coding and teleportation) Lecture 2 Circuits, reversible computation, and universality Lecture 3 Universality continued, DiVincenzo criteria, nonlinear optics, survey of implementations Lecture 4 The Church-Turing thesis, efficiency, strong Church-Turing thesis, complexity classes, black boxes Lecture 5 Introductory quantum algorithms: Deutsch-Jozsa and Simon's problem Lecture 6 The quantum Fourier transform and phase estimation Lecture 7 Factoring, RSA, Shor's algorithm and order finding Lecture 8 Searching algorithms Lecture 9 Open quantum systems Lecture 10 Distance measures and entropy Lecture 11 Compression Lecture 12 Error correction Lecture 13 Stabilizer codes and fault tolerance Lecture 14 Quantum key distribution 《Perimeter Scholars International (PSI) 2013-2014》 Full Programme: ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbOHCtm9n3woen7IPkYcw9So Mathematics Review / Front End Courses: ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbOVlHBkf2sicIwt-OVLd9sa Core Topics (1)-(6): Foundational subjects. (Three three-week sessions, each with two courses running in parallel.) 1. Relativity (PHYS 604) - Neil Turok (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbMoUXv4-vHVTekVsfqjvUS3 2. Quantum Theory (PHYS 605) - Joseph Emerson (Waterloo) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbNhfcvz10uBUhmrNghZbOdw 3. Statistical Mechanics (PHYS 602) - Anton Burkov (Waterloo) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbNzBPtYEQiOdjZjvA29_Orm 4. Quantum Field Theory I (PHYS 601) - Freddy Cachazo (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbNQzeqBviLxc5yx7ZhIDpcd 5. Quantum Field Theory II (PHYS 603) - Francois David (CEA, Saclay) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbN12HNCCDneCDMfRJzhyzW9 6. Condensed Matter I (PHYS 611) - Roger Melko (Waterloo), Xiao-Gang Wen (Perimeter), Anushya Chandran (Boston) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbPqgdbJ3jeI31gTGd77Mq51 Reviews (7)-(15): Subdisciplinary subjects. (Three three-week sessions, each with three courses running in parallel. Students are required to take at least four review courses.) 7. Standard Model (PHYS 622) - Paul Langacker (IAS, Princeton) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbMwftn7CtcFirLgrmW_SvqU 8. Gravitational Physics (PHYS 636) - Ruth Gregory (Durham) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbPOKRqGyUiVDFb5Mkj_GGPP 9. Foundations of Quantum Mechanics (PHYS 639) - Lucien Hardy & Matthew Pusey (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbPZ_janKlNOKaqrbTNHhEZu 10. Condensed Matter II (PHYS 637) - Alioscia Hamma (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbPfy98V0PKLMGbq36lg7sbM 11. String Theory (PHYS 623) - Davide Gaiotto (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbNTN201q7pUNuikPVsow5DA 12. Cosmology (PHYS 621) - Latham Boyle (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbMrbnwdZ9XgIX0j0w4G-cM7 13. Beyond the Standard Model (PHYS 777) - Robert Mann (Waterloo) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbPYhtU_c_mO3qOKpHrRxiwi 14. Quantum Gravity (PHYS 638) - Bianca Dittrich (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbOmi3YyleA8GrVaKQ1zP9uV 15. Quantum Information (PHYS 635) - Andrew Childs (Maryland) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbOSAZy4zsHlO2Az61tnb_gQ Explorations (16)-(20): Short, in-depth courses on specialized fields which are currently "hot". (Three three-week sessions, each with three courses running in parallel. Students are required to take at least two exploration courses.) 16. Explorations in Quantum Information (PHYS 641) - David Cory (Waterloo) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbOmQnEjG7z_u9stsdVbxHho 17. Explorations in Condensed Matter - Guifre Vidal (Perimeter) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbOh-CbTK8lBfYMtetPmA5-c 18. Explorations in String Theory (PHYS 647) - Andrei Starinets (Oxford) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbMp6tZVSw7yCcpp-VDnRV7M 19. Explorations in Particle Theory (PHYS 646) - Brian Shuve (Harvey Mudd College) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbN-oyHDtEc9peTmmjGh3fx2 20. Explorations in Cosmology (PHYS 649) - Matthew Johnson (York) ▶ https://www.youtube.com/playlist?list=PLFMKfDJ8QzbO92JCGRDPCZm5wbJ4rbgiw
Views: 234 Centre for Mathematical Sciences
John Preskill, Richard P. Feynman Professor of Theoretical Physics at the California Institute of Technology, gave a lecture about Introduction to Quantum Information. The lecture is the first of two parts, and was filmed at the Canadian Summer School on Quantum Information, held at the University of Waterloo in June of 2012. Find out more about IQC! Website - https://uwaterloo.ca/institute-for-quantum-computing/ Facebook - https://www.facebook.com/QuantumIQC Twitter - https://twitter.com/QuantumIQC
Views: 42715 Institute for Quantum Computing
How did the field of quantum mechanics come about in the first place? The Rayleigh-Jeans catastrophe, also known as the ultraviolet catastrophe was a prediction by the Rayleigh-Jeans law that a blackbody would radiate infinite amounts of ultraviolet light. It wasn’t until Max Planck came along and predicted that light came in packets or quanta that the field of quantum mechanics emerged and unintentionally solved the ultraviolet catastrophe. Help us translate our videos! http://www.youtube.com/timedtext_cs_panel?c=UC7DdEm33SyaTDtWYGO2CwdA&tab=2 Creator: Dianna Cowern Editor: Jabril Ashe Writer: Sophia Chen Animations: Jabril Ashe/Kyle Norby Thanks to Ashley Warner and Kyle Kitzmiller http://physicsgirl.org/ http://twitter.com/thephysicsgirl http://facebook.com/thephysicsgirl http://instagram.com/thephysicsgirl Subscribe to Physics Girl for more fun physics! Music: APM
Views: 502877 Physics Girl
Want to learn how to program a quantum computer using Cirq? In this episode of QuantumCasts, Dave Bacon (Twitter: @dabacon) teaches you what a quantum program looks like via a simple “hello qubit” program. You’ll also learn about some of the exciting challenges facing quantum programmers today, such as whether Noisy Intermediate-Scale Quantum (NISQ) processors have the ability to solve important practical problems. We’ll also delve a little into how the open source Python framework Cirq was designed to help answer that question. Follow these instructions to install Cirq → http://bit.ly/2IermSw Need to catch up? Watch every episode of QuantumCasts here → http://bit.ly/2Pw0xay Learn about the Google AI Quantum team → http://bit.ly/2DnvKLy Subscribe to the TensorFlow channel→ http://bit.ly/TensorFlow1
Views: 5907 TensorFlow
Fabian Furrer of Institut für Theoretische Physik, Universität Hannover and the University of Tokyo presented: Continuous variable entropic uncertainty relations in the presence of quantum memory on behalf of his co-authors Mario Berta (Institut für Theoretische Physik, ETH Zürich), Matthias Christandl (Institut für Theoretische Physik, ETH Zürich), Volkher Schultz (Institut für Theoretische Physik, ETH Zürich) and Marco Tomamichel (Centre for Quantum Technologies, National University of Singapore) at the 2013 QCrypt Conference in August. http://2013.qcrypt.net Find out more about IQC! Website - https://uwaterloo.ca/institute-for-quantum-computing/ Facebook - https://www.facebook.com/QuantumIQC Twitter - https://twitter.com/QuantumIQC
Views: 439 Institute for Quantum Computing
In this talk I will survey a recently introduced cryptographic problem called Learning with Rounding (LWR). I will show reductions from and to the more well-established Learning with Errors (LWE) problem, and demonstrate the applicability of LWR to the construction of efficient Pseudorandom Functions and other cryptographic primitives.
Views: 234 Microsoft Research
Falling down the rabbit hole a bit further on the "first quantum computers" that Yale is claiming to be making on 11.14.2017 which is bull because of the DWave. What gives?? Following the money trail with a special guest appearance by Elon Musk at the Sequoia venture capital firm. Part 1: https://www.youtube.com/watch?v=Dqt06uRNFmQ&t=25s Quantum Circuits, Inc.: http://quantumcircuits.com/ An API for quantum computing in the cloud: https://www.rigetti.com/ Tweet Sequoia!! https://twitter.com/sequoia Send Love Not Hate: [email protected] Tags: Conspiracy Theory/Theories Mandela Effect Time Travel Quantum Physics Quantum Mechanics D-Wave Computers CERN Pseudo-Science/Religion Alternate Reality/Realities Alternate Dimensions Multiple Universes Multi-Verse Theory Smart Grid 5G Internet of Things Internet of Everything Agenda 21 (omg do I need more tags?? :) Thanks for taking the time To watch! (and read) UNLESS OTHERWISE NOTED, I DO NOT OWN NOR TAKE CREDIT FOR IMAGES AND/OR VIDEO USED for educational purposes only. "Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use."
Views: 210 The Edge Of Here
First part in an interview series with Scott Aaronson - this one is on quantum computing - future segments will be on Existential Risk, consciousness (including Scott's thoughts on IIT) and thoughts on whether the universe is discrete or continuous. See 'Complexity-Theoretic Foundations of Quantum Supremacy Experiments' https://www.scottaaronson.com/papers/quantumsupre.pdf Transcript: http://www.scifuture.org/the-winding-road-to-quantum-supremacy-scott-aaronson/ Bio : Scott Aaronson is a theoretical computer scientist and David J. Bruton Jr. Centennial Professor of Computer Science at the University of Texas at Austin. His primary areas of research are quantum computing and computational complexity theory. He blogs at Shtetl-Optimized: https://www.scottaaronson.com/blog/ #quantumcomputing #physics #computing #quantumsupremacy Many thanks for watching! Consider supporting SciFuture by: a) Subscribing to the SciFuture YouTube channel: http://youtube.com/subscription_center?add_user=TheRationalFuture b) Donating - Bitcoin: 1BxusYmpynJsH4i8681aBuw9ZTxbKoUi22 - Etherium: 0xd46a6e88c4fe179d04464caf42626d0c9cab1c6b - Patreon: https://www.patreon.com/scifuture c) Sharing the media SciFuture creates: http://scifuture.org Kind regards, Adam Ford - Science, Technology & the Future
Views: 2941 Science, Technology & the Future
Tuesday, 24 Feb. 2015 IDEA League Quantum Information Processing School, RWTH Aachen University
Views: 910 IDEA League 2015
Helger Lipmaa (Tartu Universitāte) referāts "Succinct Non-Interactive Zero Knowledge Arguments from Span Programs and Linear Error-Correcting Codes", Recently, Gennaro, Gentry, Parno and Raykova [GGPR12] proposed an ecient non-interactive zero knowledge argument for Circuit-SAT, based on non-standard notions like conscientious and quadratic span programs. We propose a new non-interactive zero knowledge argument, based on a simple combination of standard span programs (that verify the correctness of every individual gate) and high-distance linear error-correcting codes (that check the consistency of wire assignments). We simplify all steps of the argument. As one of the corollaries, we design an (optimal) wire checker, based on systematic Reed-Solomon codes, of size 8n and degree 4n, while the wire checker from [GGPR12] has size 24n and degree 76n, where n is the circuit size. Importantly, the new argument has constant verier's computation. (publikācija: http://eprint.iacr.org/2013/121) Kvantu un kritpo diena 2013 (Quantum and Crypto Day 2013) Latvijas Universitātes Datorikas fakultātē notika 2013. gada 25. aprīlī. Plašāka informācija: http://www.df.lu.lv/zinas/t/20343/
Views: 997 Latvijas Universitāte
Prof. Shoucheng Zhang discusses three pillars of information technology: quantum computing, AI and blockchain. He presents the fundamentals of crypto-economic science, and answers questions such as: What is the intrinsic value of a medium of exchange? What is the value of consensus and how does it emerge? How can math be used to create distributed self-organizing consensus networks to create a data-marketplace for AI and machine learning? Prof. Zhang is the JG Jackson and CJ Wood professor of physics at Stanford University. He is a member of the US National Academy of Science, the American Academy of Arts and Sciences and a foreign member of the Chinese Academy of Sciences. He discovered a new state of matter called topological insulator in which electrons can conduct along the edge without dissipation, enabling a new generation of electronic devices with much lower power consumption. For this ground breaking work he received numerous international awards, including the Buckley Prize, the Dirac Medal and Prize, the Europhysics Prize, the Physics Frontiers Prize and the Benjamin Franklin Medal. He is also the founding chairman of DHVC venture capital fund, which invests in AI, blockchain, mobile internet, big data, AR/VR, genomics and precision medicine, sharing economy and robotics.
Views: 91018 Talks at Google
Moore's Law -- putting more and more transistors on a chip -- accelerated the computing industry by so many orders of magnitude, it has (and continues to) achieve seemingly impossible feats. However, we're now resorting to brute-force hacks to keep pushing it beyond its limits and are getting closer to the point of diminishing returns (especially given costly manufacturing infrastructure). Yet this very dynamic is leading to "a Cambrian explosion" in computing capabilities… just look at what's happening today with GPUs, FPGAs, and neuromorphic chips. Through such continuing performance improvements and parallelization, classic computing continues to reshape the modern world. But we're so focused on making our computers do more that we're not talking enough about what classic computers can't do -- and that's to compute things the way nature does, which operates in quantum mechanics. So our smart machines are really quite dumb, argues Rigetti Computing founder and CEO Chad Rigetti; they're limited to human-made binary code vs. the natural reality of continuous variables. This in turn limits our ability to work on problems that classic computers can't solve, such as key applications in computational chemistry or large-scale optimization for machine learning and artificial intelligence. Which is where quantum computing comes in. SUBCRIBE - https://goo.gl/aiECKP The a16z Podcast discusses tech and culture trends, news, and the future -- especially as ‘software eats the world’. It features industry experts, business leaders, and other interesting thinkers and voices from around the world. This podcast is produced by Andreessen Horowitz (aka “a16z”), a Silicon Valley-based venture capital firm. Multiple episodes are released every week; visit a16z.com for more details.
Views: 247 a16z - Andreessen Horowitz
Quantum computers exploit the bizarre features of quantum mechanics to perform tasks that are impossible using conventional means. Sending instantaneous messages across long distances or quickly computing over ungodly amounts of data are just two possibilities that arise if we can design computers to exploit quantum uncertainty, entanglement, and measurement. In this SFI Community Lecture, scientist Christopher Monroe describes the architecture of a quantum computer based on individual atoms, suspended and isolated with electric fields, and individually addressed with laser beams. This leading physical representation of a quantum computer has allowed demonstrations of small algorithms and emulations of hard quantum problems with more than 50 quantum bits. While this system can solve some esoteric tasks that cannot be accomplished in conventional devices, it remains a great challenge to build a quantum computer big enough to be useful for society. But the good news is that we don’t see any fundamental limits to scaling atomic quantum computers, and Monroe speculates as to how this might happen. Christopher Monroe is a leading atomic physicist and quantum information scientist. He demonstrated the first quantum gate realized in any system at the National Institute of Standards and Technology (NIST) in the 1990s, and at University of Michigan and University of Maryland he discovered new ways to scale trapped ion qubits and simplify their control with semiconductor chip traps, simplified lasers, and photonic interfaces for long-distance entanglement. He received the American Physical Society I.I. Rabi Prize and the Arthur Schawlow Laser Science Prize, and has been elected into the National Academy of Sciences. He is Co-Founder and Chief Scientist at IonQ in College Park, MD.
Views: 1028 Santa Fe Institute
Chris Erven of the University of Bristol presented: An experimental implementation of oblivious transfer in the noisy storage model on behalf of his co-authors Stephanie Wehner (National University of Singapore), Nick Gigov, Raymond Laflamme (Institute for Quantum Computing) and Gregor Weihs (University of Innsbruck) at the 2013 QCrypt Conference in August. http://2013.qcrypt.net. Find out more about IQC! Website - https://uwaterloo.ca/institute-for-quantum-computing/ Facebook - https://www.facebook.com/QuantumIQC Twitter - https://twitter.com/QuantumIQC
Views: 265 Institute for Quantum Computing
what the science Quantum computer, another sci-fi word or the future reality....watch to find out The first computer was made in the year 1949. Which was called ENIC, electronic numerical integrator and computer. It was so huge that it took an entire floor or two, and at the same time, it was very slow and less powerful as compared to the modern-day computers. But as the time went by computers had become smaller and smarter, this reduction of size will continue and soon the Morden day computers will reach its physical limit. Here is where quantum computers come in, These computers will be extremely powerful and will also help to create smaller and more powerful computers. Please do like share and subscribe. Subscribe: https://www.youtube.com/channel/UClFHOffx2_DpPHNz2WdvQsA Facebook page: https://www.facebook.com/wtsavk/ Twitter: https://twitter.com/wts_avk
Views: 466 What The Science
Claude Shannon - colossus of Information Theory. Entropy. The term was coined to describe a quantity that arose in the laws of Thermodynamics, and is often summarised as being a measure of disorder. One of Shannon's great insights was to see that this term could be used to describe the unpredictability of signals. Information. This term was chosen by Shannon to describe what is sent by signalling a message from one location to another. He defines it strictly and he does not include meaning in the definition, but rather the density of information is judged by it's lack of redundancy, its unpredictability. Randomness. Another concept which sounds deceptively simple, but which requires careful definition for mathematicians to tap into its power. A number is random if it is not possible to write an instruction to produce it that is shorter than writing out the number itself in full. Thus a number such as 11111111111111111 is not random because you can say "17 ones" and capture it. But also a number that looks random such as the decimal places of pi, may not be. There is a mathematical recipe for pi that you can tell someone to work out to get pi to any desired level of accuracy. As yet no one has detected any pattern to the decimal places of the number. The recipe is "Take 4, subtract 4/3, add 4/5, subtract 4/7 etc etc" it gets closer and closer to pi as you keep adding and subtracting smaller bits. Complexity. Similar to randomness, but where they can differ in certain contexts is in recognising "logical depth" Charles Bennett defined logical depth thus "What might be called its buried redundancy - parts predictable only with difficulty, things the receiver could in principle have figured out without being told, but only at considerable cost in money, time, or computation." The term can be used to convey the quality that holds the greatest amount of meaning for us in a message. Noise. Noise is not just the result of faulty design or construction of communication equipment, it is a fundamental property of electrical components. The equations that describe it were derived by Albert Einstein to describe Brownian motion - the movement of microscopic pollen in water that had been a puzzle until Einstein published his paper in 1905 (the same year he published the 'special relativity' and the 'electrostatic effect' papers - quite a year) Shannon's noisy coding theorem shows that error correction can effectively counter noise and corruption, at the cost of redundancy and extra computation.
Views: 627 John Harmer
Quantum computing holds the promise to enormously increase computing performance in areas including cryptography, optimization, search, quantum chemistry, materials science, artificial intelligence, machine learning, personalized medicine and drug discovery. Quantum computing hardware is maturing swiftly. Depending on the expert you talk with, quantum computing is around the corner or a few years away. Concurrently, research on algorithms that take advantage of quantum computing is also moving briskly. In this discussion, panelists will look at where we are in both theory and practice, where we are headed, and what quantum skills the average computer scientist will eventually need. Moderator: Umesh Vazirani, University of California, Berkeley Panelists: Dorit Aharonov, Hebrew University of Jerusalem Jay M. Gambetta, IBM Research John Martinis, Google and University of California, Santa Barbara Andrew Chi-Chih Yao (2000 Turing Laureate), Tsinghua University
Views: 2756 Association for Computing Machinery (ACM)
What does qudit mean? A spoken definition of qudit. Intro Sound: Typewriter - Tamskp Licensed under CC:BA 3.0 Outro Music: Groove Groove - Kevin MacLeod (incompetech.com) Licensed under CC:BA 3.0 Intro/Outro Photo: The best days are not planned - Marcus Hansson Licensed under CC-BY-2.0 Book Image: Open Book template PSD - DougitDesign Licensed under CC:BA 3.0 Text derived from: http://en.wiktionary.org/wiki/qudit Text to Speech powered by TTS-API.COM
Views: 64 What Does That Mean?
How many queries are needed to determine a polynomial F(X)? We look at this question when F(X) is defined over a finite field GF(q) and has degree d, such that d+1 queries are obviously sufficient. Shamir's Secret Sharing protocol is based on the result that d+1 classical queries are also needed as no interpolation is possible based on only d values of F. Here we look at how many quantum queries are sufficient to perform the same task. Earlier work by [Kane & Kutin 2009] and [Meyer & Pommersheim 2010] proved that at least d/2+1/2 quantum queries are needed, while [Boneh and Zhandry 2012] showed that d quantum queries are sufficient. In this talk we will describe a quantum algorithm that uses only d/2+1/2 queries and that has a constant success probability. Our algorithm relies on the analysis of the classical Moment Problem defined over finite fields. (Joint work with Andrew Childs)
Views: 139 Microsoft Research
Sparse Permutations with Low Differential Uniformity
Views: 89 Institut Fourier
A Google TechTalk, June 29, 2016, presented by Oleksandr Kyriienko (Niels Bohr Institute) ABSTRACT: The successful application of a quantum annealing procedure largely relies on the possibility to implement a non-trivial Hamiltonian in a fully controlled system. The circuit QED platform has shown a tremendous progress in this direction, demonstrating qubit chains with on-site effective magnetic fields being tunable in time along any chosen axis. At the same time, the inter-qubit interaction is typically limited to the isotropic XY model with nearest neighbor flip-flop process, which limits accessible types of Hamiltonian which can be simulated. Typically, surmounting of this restriction requires either construction of unconventional couplings between qubits or digitization of the evolution. We propose to use Floquet dynamics to perform a quantum simulation with superconducting system. The algorithm relies on fast time modulation of an effective magnetic field for the qubits, such that the resulting time-averaged Floquet Hamiltonian is of the generic Heisenberg XYZ type, and is controllable by the drive parameters. As examples we show recipes for designing transverse Ising and non-stoquastic XYZ Hamiltonians, and perform annealing to the ground state of each configuration. Considering realistic parameters the procedure allows closely following the ideal continuous annealing, yielding a fidelity corresponding to the one achievable by digital evolution with many (greater than 20) Trotter steps. The scheme does not require modification of existing circuit QED setups, potentially allows for diverse high fidelity quantum annealing with currently accessible system parameters, and can serve as simple yet reliable way towards quantum annealing with limited resources. Anders S. Sørensen, Niels Bohr Institute Presented at the Adiabatic Quantum Computing Conference, June 26-29, 2016, at Google's Los Angeles office.
Views: 388 GoogleTechTalks