#quantum ibm computing

[harrelltut]

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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[wikipediapictures]

IBM Q System One

[sspacegodd]

Quantum computer.

[mysteriousquantumphysics]

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

[tundraglitch]

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.

[emerging-tech]

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…

[govindhtech]

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.

Read more on Govindhtech.com

[averycanadianfilm]

The company announces its latest huge chip — but will now focus on developing smaller chips with a fresh approach to ‘error correction’.

[eannpatterson]

Chirping while calculating probabilities

A couple of weeks ago, I visited the London headquarters of IBM in the UK and Ireland for discussions about possible areas of collaboration in research and education.  At the end of our meeting, we were taken to see some of their latest developments, one of which was their Quantum System One computer.  We had seen its casing, a shiny silver cylinder about half metre in diameter and a metre and…

[harrelltut]

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IMMORTAL U.S. MILITARY KING SOLOMON-MICHAEL HARRELL, JR.™

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[quantimist]

Quantum Computing with Qiskit Free Course | 1 Year | Q World

Exciting News: QWorld’s QClass23/24 Your Gateway to Quantum Computing! Are you ready to dive into the fascinating world of quantum computing, algorithms, and programming? Look no further! QWorld is thrilled to announce the launch of our two-semester-long QClass23/24, beginning in September 2023 and running until May 2024. Join us for an immersive virtual experience that will equip you with the…

[eveningnetwork]

Quantum Computing Advance Begins New Era, IBM Says

Calculatoarele cuantice de astăzi au o gamă de calcul mică, cu cipuri în interiorul smartphone-urilor conținând miliarde de tranzistori, în timp ce cele mai puternice computere cuantice conțin sute de tranzistori cuantici echivalent. De asemenea, sunt nesiguri. Dacă faceți același calcul din nou și din nou, este probabil să obțineți un răspuns diferit de fiecare dată. Calculatoarele cuantice,…

[innonurse]

Cleveland Clinic and IBM present the world's first quantum computer devoted to healthcare research

- By InnoNurse Staff -

On March 20, Cleveland Clinic and IBM announced the first onsite private sector IBM-managed quantum computer deployment in the United States. 

The IBM Quantum System One deployed at Cleveland Clinic will be the world's first quantum computer dedicated only to healthcare research, with the goal of assisting Cleveland Clinic in accelerating biomedical discoveries.

Read more at IBM/PRNewswire

///

Other recent news and insights

Based on the results of routine hospital testing, machine learning techniques forecast the probability of mortality (University of Alberta)

The first FDA-approved AI-assisted colonoscopy tool to support doctors in detecting polyps that can lead to colorectal cancer (Medtronic plc/PRNewswire)

[mufawad]

Earthquake in Turkey, New approach to Quantum computing, New treaty for Pandemics and other Science events of the Week

In today's blog, you will read about:

· The devastating earthquake that hit Turkey and Syria; · The new approaches to quantum computing; · A new treaty that will ensure equality in next pandemic; · How did Neanderthals hunt mammoths; · The extreme use of antibiotics in animals and poultry; · Histones found in bacteria for the first time; Read More

[sifytech]

Resistance is futile: Why businesses must fully embrace AI

Artificial Intelligence may have come a long way but many Indian businesses still resist it writes Satyen K. Bordoloi explaining why they should go the other way Read More. https://www.sify.com/ai-analytics/resistance-is-futile-why-businesses-must-fully-embrace-ai/

[mihirjaiswal]

Quantum Computing through a physicist’s eye: An Interview with Dr Shangjie Guo

This is a physicist’s interview. A physicist who is trying not to be a physicist for the good of the world. I challenged Dr Shangjie Guo to explain the complicated concepts buried within the field of quantum computing and he took on that challenge. The result is this interview. He is a PhD in quantum computing from the University of Maryland, College Park and a practitioner of quantum computing. His knowledge about the software, hardware, theory, application, challenges, opportunities of quantum computing is profound. Find the excerpts from his interview before it becomes a book in a few months.

Mihir: The concept of qubit. A bit has only two states: 0 and 1. A qubit has more than two states. By nature, a qubit is more powerful than a bit. Is that true?

Shangjie: While it's true that qubits, the basic units of quantum information, can exist in a state of superposition and represent both 0 and 1 simultaneously, this doesn't necessarily make them 'more powerful' when the No. qubits is small. Let me clarify with an analogy. If you flip a coin and don't observe the outcome, it exists in a state similar to a qubit's superposition - it could be heads or tails. It only settles into a definite state when we observe it. So, a single qubit isn't vastly more powerful than a probabilistic bit. The power of quantum computing emerges when you have multiple qubits that are entangled, meaning the state of one qubit is related to the state of another via multi-qubit gates. 

Mihir: You talked about gates there. In classical computing we have gates like AND, OR, NOT. In quantum computing, we have CNOTGate or HGate. Fundamentally, is the concept of gate similar in classical and quantum computing?

Shangjie:  Yes, the basic idea behind gates in both classical and quantum computing is quite similar. Gates in both scenarios perform operations on bits or qubits. However, in quantum computing, operations can be more complex due to the principles of superposition and entanglement. Quantum gates manipulate qubits in ways that can give certain computational advantages, i.e. gates counts are considerably less, especially for complex algorithms. 

Mihir: Let’s pivot to the hardware. A limitation that we are approaching in classical computing is hardware. We can’t squeeze the size of chips anymore and we have to keep stacking them to achieve more power. How does quantum computing hardware differ in breaching that limitation?

Shangjie: From an architecture point of view, some quantum computing hardware can be quite different from classical hardware and some are not. For example, we have superconducting and semiconducting qubits. Those qubits are fabricated in a similar (and of course more advanced) way we build integrated circuit boards.However, superconducting qubits need to be cooled down to extremely low temperatures to function, we are talking about just a few milliKelvins. There's also an alternative approach which involves trapping and controlling ions and neutral atoms in a vacuum chamber using lasers and magnetic fields, or using integrated photonic chips. Each approach has its own challenges and benefits. 

Mihir: And each ion becomes one qubit?

Shangjie: Actually, we can view some of the energy levels of the electrons associated with those ions as qubits. These energy levels allow us to store and manipulate quantum information. 

Mihir: Can you really control how many qubits are going to be in such a system?

Shangjie: Yes, it's possible to control the number of qubits in a system. However, it can become complex when you have many qubits. For instance, interactions among qubits, such as 'crosstalk noise', can become a significant issue.

Mihir: My introduction to classical computing was through pascal language and had a little exposure to assembly programming. Classical computing evolved big time to low level languages and high level advanced languages. Many quantum programming is python based these days. Does that mean we skipped the equivalent of assembly programming and started with high level programming in quantum computing?

Shangjie: Actually, we're still in the early stages of quantum programming. Even though we often use high-level languages like Python, the operations we're performing are quite basic. We're essentially controlling the quantum state, gate by gate, which is analogous to low-level programming in the classical sense. We are still trying to figure out the best ways to control and manipulate quantum states. 

Mihir: You did your PhD in quantum computing. How many years did you study quantum computing?

Shangjie: I studied quantum computing as a PhD student for six years.

Mihir: Was there enough information then to study quantum computing for six years? Being a program, there were multiple people doing a PhD in quantum computing. Was there enough basic information available and opportunity for multiple PhDs in the field?

Shangjie: During my PhD, the focus of research in quantum computing was mostly on its foundational aspects. One part was about actually building a functioning quantum computer, while the other was about finding potential applications assuming such a computer existed. Both of these areas were, and still are, rich in research opportunities. 

Mihir: When am I getting a quantum computer on my desktop?

Shangjie: It might be quite a while before we see quantum computers on our desks, if ever. Quantum computers are specialized machines that require specific conditions to operate, such as a cryogenic vacuum chamber as we mentioned before. They're also not designed for everyday tasks like browsing the web or writing emails, but for solving complex computational problems such as optimizing traffic or designing enzymes. Therefore, it's more likely that we'll access quantum computing power through cloud services. 

Mihir: Can I really trust a quantum computer on cloud that it is indeed a quantum computer and not a quantum simulator running on classical computing?

Shangjie: Verifying that a machine is a genuine quantum computer is indeed a challenge for mathematicians. There's a field of study called quantum verification that is working on this very problem. One intuitive potential approach could be to compare results from multiple quantum computing services to check for consistency. 

Mihir: Quantum mechanics and quantum chemistry have been using approximations to do quantum calculations for decades now. How do the current quantum algorithms differ from them? Why can’t we use those same algorithms in quantum computing?

Shangjie: The quantum algorithms used in quantum computing seek to take advantage of the inherent properties of quantum mechanics more fully than the approximate methods used in quantum chemistry and other fields. By relaxing those approximations, they aim to perform larger and more accurate calculations. 

Mihir: Is the key to success in quantum computing in future is better hardware or better software?

Shangjie: The development of quantum computing needs advances in both hardware and software. We need more efficient algorithms that can exploit the potential of quantum hardware, and for such algorithms, we need more powerful and reliable quantum hardware. However, in my view, finding an efficient quantum algorithm for a practical use case is currently a more pressing issue, because that solution could guide us to design quantum hardware with an existing market.  

Mihir: And my last question, what talent is going to define the success of quantum computing in the near future?

Shangjie: It might surprise you, but I believe that project management skills will be crucial. I know that you are a program manager, and I found that there's a need for professionals like you who can bring together diverse teams, define clear goals, and manage resources efficiently. Quantum computing is a complex and interdisciplinary field, and coordinating efforts effectively can significantly impact its advancement.

Further Reading Suggested by Dr. Shangjie Guo

QUTAC use case report, how QC can be used

Essential Hardware Components of a Quantum Computer

The Rise of Quantum Computing

Quantum Computing Hype is Bad for Science

Navigate Through the Quantum Mist