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harrelltut · 1 year ago

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I.B.1698 MICHAEL [IBM] harrelltut.com Domain Computer [D.C.] DEFENSE.gov of SIRIUS BLACKANUNNAQI.tech Patents 2 applesoftbasic.com of CLASSIFIED 1978 Deutsch applesoftbasic.tech Machine Application Configurations [MAC] Automatically Programing [MAPPING] Tri-Solar Black Sun planetrizq.tech Languages from kingtutdna.com’s Highly Complex [ADVANCED] Ancient Hi:tKEMETICompu_TAH [PTAH] MOON Universe [MU] of HIGH LEVEL DATA LINK CONTROL [HLDC] Services 2 Constellation ORION’s Interplanetary quantumharrell.tech Earth [Qi] HOLOGRAM HARDWARE of Arithmetic Logic [H.A.L.] Unit Operations Remotely Controlling iapplelisa.tech’s HIGH ENERGY RADIO [HER] FREQUENCY WEAPONS BLASTING HIGH-INTENSITY RADIO WAVES 2 ALL ELECTRONICS on Earth [Qi] from Astronomical MERCURY’s ibmapple1984.tech Secure Socket Layer Virtual Private Network [SSL VPN] Communications.gov Privately Managed [PM] by ANU GOLDEN 9 Ether [iAGE] quantumharrell.tech Graphical User Interface [GUI] Domain Compu_TAH [PTAH] of iquantumapple.com Infrastructure as a Service [IaaS] since quantumharrelltech.com’s Hypertext Transfer Protocol [HTTP] Digitally Control [D.C.] Tri-Solar Black Sun planetrizq.tech’s EXTREME WEATHER MACHINE by Engineering [ME] AutoCAD [MAC] Robotics in Architectural Memory Equipment w/Symmetric Encryptions of Satellite [RAMESES] Broadband Communication [B.C.] quantumharrellmatrix.tech Languages @ 1921 QUANTUM 2023 HARRELL 2024 TECH 2025 Apple & IBM [A.i.] LLC of ATLANTIS [L.A.] 5000

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© 1968-2223 QUANTUM HARRELL TECH LLC All Private Apple, Inc. [A.i.] Domain [AID] Name Rights Reserved. | 1968-2223 QUANTUM HARRELL TECH LLC All Pentagon DotCom defense.gov Department Domain Rights Reserved.

#ibm #apple #apple patents #quantumharrelltech #quantum apple computing #quantum ibm computing #u.s. michael harrell #harrelltut.com #kingtutdna.com #schwarzer deutscher ökonom

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wikipediapictures · 10 months ago

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IBM Q System One

#ibm q system one #quantum computing #quantum computer #ibm #wikipedia #wikipedia pictures #tech #technologycore #techcore #technology #International Business Machines Corporation #computer science #computer engineering

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sspacegodd · 2 years ago

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Quantum computer.

#quantum computer #ibm

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mysteriousquantumphysics · 2 years ago

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Cutting Quantum Circuits into Pieces - why and how?

Even though quantum computing is a promising and huge field, it is still at an early development stage. We know algorithms with clear advantage towards classical algorithms such as Grover's or Shor's - however, we are far away from implementing those algorithms on real devices for e.g. breaking state of the art RSA encriptions.

Today's Possibilities of Quantum Computing

Thus, part of current research is to make use of the kind of quantum computers which are available today: Noisy Intermediate-Scale Quantum (NISQ) devices. They are far away from ideal quantum computers since they provide only a limited number of qubits, have faulty gate implementations and measurements and the quantum states decohere rather fast [1]. As a result, algorithms which require large depth circuits cannot be realistically implemented nowadays. Instead, it is advisable to find out what can be done with the currently available NISQ devices. Good candidates are variational quantum algorithms (VQA) in which one uses both quantum and classical methods: One constructs a parametrized quantum circuit whose parameters are optimized by a classical optimizer (e.g. COBYLA). To those methods belong for instance the variational quantum eigensolver (VQE) which can be used to find the ground state energy of a Hamiltonian (a problem which is in general often tackled without quantum computing, i.e. classical computing with tensor network approaches). Another method is solving QUBO problems with the quantum approximate optimization algorithm (QAOA). These are promising ideas, but one should note that it is not sure yet whether we can obtain quantum advantage with them or not [2].

Cutting Quantum Circuits

So far, we have learned that current quantum devices are faulty, hence still far away from fault-tolerant quantum computers. Thus, it is preferable to make quantum circuits of the above mentioned VQAs smaller somehow. Imagine the case in which you want to use the ibm_cairo system with 27 quibts, but the problem you want to solve requires 50 qubits - what can you do? One prominent idea is to cut the circuit of your algorithm into pieces (in this case, bipartitioning it). How can this be done? As you can imagine, such a task requires sophisticated methods to simulate the quantum behaviour of the large circuit even though one has fewer qubits available. Let's briefly look on how this can be done.

Wire Cutting v.s. Gate Cutting

There are different ideas about where to place the cut. In some situations it might be advisable to cut a complicated gate [3, 4]. The more illustrative way is to cut one or more wires of a circuit by implementing a certain decomposition of an identity onto the wire(s) to be cut [5, 6]. In general, such a decomposition looks like

L is the space of linear operators on the d-dimensional complex vector space. How should this be understood? For example in [6] they apply a special case of this identity equation; in a run of the circuit only one of these terms (one channel) is applied at a time. This already indicates that cutting requires running the circuit multiple times in order to simulate the identity. This makes sense intuitively, since making a cut somewhere in a circuit makes it necessary to perform a measurement. As a result, some of the entanglement / quantum properties of the circuit are lost. To compensate this, one has to artifically simulate this quantum behaviour by sampling (running the circuit more often). This so-called sampling overhead can be proven to be

This can be derived with the help of defining an unbiased estimator and applying Hoeffding's inequality. A detailed derivation (which holds for general operators, not only for the identity) can be found in appendix E of [3]. The exact sampling cost depends on the explicit decomposition one wants to apply.

Closing remarks

Up to my knowledge, those circuit cutting schemes only work efficiently for special cases. Often, the cost depends on the size of the cut, i.e. how many wires are cut. Additionally, the original circuit should be able to be partitioned reasonably. In the title picture you can see a mock circuit with five qubits. You can see that on the left side of the cut, there are gates which act on the first three (1,2,3) qubits only, while on the right side they only act on qubits 3,4 and 5. Hence, the cut should be placed on the overlap on both parts, i.e. on the middle qubit (3). The cut size is only one in this case, but in useful applications the cut size might be much larger. Since the cost often depends on the dimension of the cut qubits, the cost increases exponentially in the cut size (since the Hilbert space dimension grows as 2^k for the number of cuts k).

Thus, we see that circuit cutting can be very powerful in special problem instances, in which it can e.g. reduce the required qubits roughly by half - this helps making circuits shallower and smaller. However, there are lots of limitation given by the set of suitable problem instances and the sampling overhead.

--- References

[1] Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl, Julian Obst, Felix Truger, Benjamin Weder. Investigating the effect of circuit cutting in QAOA for the MaxCut problem on NISQ devices. 2023. arXiv:2302.01792

[2] M. Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, Patrick J. Coles. Variational Quantum Algorithms. 2021. arXiv:2012.09265

[3] Christian Ufrecht, Maniraman Periyasamy, Sebastian Rietsch, Daniel D. Scherer, Axel Plinge, Christopher Mutschler. Cutting multi-control quantum gates with ZX calculus. 2023. arXiv:2302.00387

[4] Kosuke Mitarai, Keisuke Fujii. Constructing a virtual two-qubit gate by sampling single-qubit operations. 2019. arXiv:1909.07534

[5] Tianyi Peng, Aram Harrow, Maris Ozols, Xiaodi Wu. Simulating Large Quantum Circuits on a Small Quantum Computer. 2019. arXiv:1904.00102

[6] Angus Lowe, Matija Medvidović, Anthony Hayes, Lee J. O'Riordan, Thomas R. Bromley, Juan Miguel Arrazola, Nathan Killoran. Fast quantum circuit cutting with randomized measurements. 2022. arXiv:2207.14734

#mysteriousquantumphysics #physics #quantum physics #quantum computing #quantum circuit #education #women in science #science #science studyblr #quantum science #physicsblr #circuit cutting #qaoa #vqa #vqe #ibm

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tundraglitch · 1 year ago

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Free Courses on IBM Quantum Learning

IBM has launched a series of free course for learning the basics of quantum computing and how to use the IBM Quantum services (here the link).

At the moment I��m writing there are four courses:

Basics of quantum information

First unit in the series, the course explains the basis of quantum computing at a detailed mathematical level, it requires knowing a bit of linear algebra, but also fascinating subjects like: quantum teleportation (no, sadly it’s not like Star Trek) and superdense coding.

Fundamentals of quantum algorithms

This second unit explores the advantages of quantum computers over classical computers

Variational algorithm design

This course teaches how to write variational algorithms and how to use Qiskit, the IBM API for quantum computing.

Practical introduction to quantum-safe cryptography Quantum computers can do what a classical computer can’t: use brute force and be quick, so they can break common cryptography. This course teaches how to use encryption that cannot be break so easily.

#IBM Quantum Computing #Quantum Computing #quantum algorithms #quantum cryptography #Qiskit #mooc #free courses #quantum teleportation #superdense coding #IBM

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kittenkiwi · 1 year ago

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Oh yes, they look hella cool. I have one at work but most of the time there is a cover around the processor to keep it cool

Technicians for scale

why did no one tell me quantum computers looked like that

#kiwi speaks #kiwi talks #wholesome #wholesome content #quantum computing #IBM Quantum System One

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emerging-tech · 3 months ago

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Quantum Computing: How Close Are We to a Technological Revolution?

1. Introduction Brief overview of quantum computing. Importance of quantum computing in the future of technology. 2. Understanding Quantum Computing Explanation of qubits, superposition, and entanglement. How quantum computing differs from classical computing. 3. The Current State of Quantum Computing Advances by major players (Google, IBM, Microsoft). Examples of quantum computing…

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govindhtech · 11 months ago

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Cryptography’s three primary categories

Cryptography, from the Greek words meaning “hidden writing,” encrypts sent data so only the intended recipient can read it. Applications for cryptography are numerous. Cryptography is essential to our digital world and protects sensitive data from hackers and other cybercriminals, from WhatsApp’s end-to-end message authentication to legal form digital signatures to cryptocurrency mining’s CPU-draining ciphers.

One of the first cryptologists was Julius Caesar. Modern cryptosystems are more advanced yet work similarly. Most cryptosystems start with plaintext, which is encrypted into ciphertext using one or more encryption keys. The recipient receives this ciphertext. If the ciphertext is intercepted and the encryption algorithm is strong, unauthorized eavesdroppers cannot break the code. The targeted receiver can simply decipher the text with the correct decryption key.

Let’s start with robust cryptography frameworks’ key features:

Confidentiality: Only the intended recipient can access encrypted information.

Integrity: Encrypted data cannot be altered in storage or transit between sender and receiver without detection.

Non-repudiation: Encrypted information cannot be denied transmission.

Authentication: Sender, receiver, and information origin and destination are verified.

Key management: Data encryption and decryption keys (and related duties like key length, distribution, generation, rotation, etc.) are secure.

Three encryption types

Hybrid systems like SSL exist, although most encryption methods are symmetric, asymmetric, or hash functions.

Key symmetric cryptography

Symmetric key encryption, also known as private key cryptography, secret key cryptography, or single key encryption, employs one key for encryption and decryption. These systems need users to share a private key. Private keys can be shared by a private courier, secured line, or Diffie-Hellman key agreement.

Two types of symmetric key algorithms:

Block cipher: The method works on a fixed-size data block. If the block size is 8, eight bytes of plaintext are encrypted. Encrypt/decrypt interfaces usually call the low-level cipher function repeatedly for data longer than the block size.

Stream cipher: Stream ciphers convert one bit (or byte) at a time. A stream cipher creates a keystream from a key. The produced keystream is XORed with plaintext.

Symmetrical cryptography examples:

DES: IBM developed the Data Encryption Standard (DES) in the early 1970s. While it is vulnerable to brute force assaults, its architecture remains relevant in modern cryptography.

Triple DES: By 1999, computing advances made DES unsecure, however the DES cryptosystem built on the original DES basis provides protection that modern machines cannot break.

Blowfish: Bruce Schneer’s 1993 fast, free, public block cipher.

AES: The only publicly available encryption certified by the U.S. National Security Agency for top secret material is AES.

Asymmetric-key cryptography

One secret and one public key are used in asymmetric encryption. This is why these algorithms are called public key algorithms. Although one key is publicly available, only the intended recipient’s private key may decrypt a message, making public key cryptography more secure than symmetric encryption.

Examples of asymmetrical cryptography:

RSA: Founded in 1977 by Rivest, Shamier, and Adleman, the RSA algorithm is one of the oldest public key cryptosystems for secure data transfer.

ECC: ECC is a sophisticated kind of asymmetric encryption that uses elliptic curve algebraic structures to create very strong cryptographic keys.

One-way hash

Cryptographic hash algorithms convert variable-length input strings into fixed-length digests. The input is plaintext, and the output hash is cipher. Good hash functions for practical applications satisfy the following:

Collision-resistant: A new hash is generated anytime any data is updated, ensuring data integrity.

One-way: The function is irreversible. Thus, a digest cannot be traced back to its source, assuring data security.

Because hash algorithms directly encrypt data without keys, they create powerful cryptosystems. Plaintext is its own key.

Consider the security risk of a bank password database. Anyone with bank computer access, authorized or illegal, may see every password. To protect data, banks and other companies encrypt passwords into a hash value and save only that value in their database. Without the password, the hash value cannot be broken.

Future of cryptography

A quantum cryptography

Technological advances and more complex cyberattacks drive cryptography to evolve. Quantum cryptography, or quantum encryption, uses quantum physics’ natural and immutable laws to securely encrypt and transfer data for cybersecurity. Quantum encryption, albeit still developing, could be unhackable and more secure than earlier cryptographic systems.

Post-quantum crypto

Post-quantum cryptographic methods use mathematical cryptography to generate quantum computer-proof encryption, unlike quantum cryptography, which uses natural rules of physics. Quantum computing, a fast-growing discipline of computer science, might exponentially enhance processing power, dwarfing even the fastest super computers. Although theoretical, prototypes suggest that quantum computers might breach even the most secure public key cryptography schemes in 10 to 50 years.

NIST states that post-quantum cryptography (PQC) aims to “develop cryptographic systems that are secure against both quantum and classical computers, and [that] can interoperate with existing communications protocols and networks.”

The six main quantum-safe cryptography fields are:

Lattice-based crypto

Multivariate crypto

Cryptography using hashes

Code-based cryptography

Cryptography using isogeny

Key symmetry quantum resistance

IBM cryptography helps organizations protect crucial data

IBM cryptography solutions offer crypto agility, quantum-safety, and robust governance and risk policies through technology, consulting, systems integration, and managed security. End-to-end encryption tailored to your business needs protects data and mainframes with symmetric, asymmetric, hash, and other cryptography.