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Wave Systems Corp. (NASDAQ: WAVX) reduces the complexity, cost and uncertainty of data protection by starting inside the device. Unlike other vendors who try to secure information by adding layers of software for security, Wave leverages the security capabilities built directly into endpoint computing platforms themselves. Wave has been a foremost expert on this growing trend, leading the way with first-to-market solutions and helping shape standards through its work as a board member for the Trusted Computing Group.

Wave Systems

wavesystems

ABS-affiliated maritime software as a service company ABS Wavesight has unveiled a range of updates to its fleet management software, Nautical Systems. They are aimed at improving efficiencies in fleet operations, streamlining the administration of maintenance tasks and enabling more effective procurement.

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The National Hurricane Center is tracking a trough of low pressure over the eastern Caribbean Sea."This system is expected to move westward during the next several days, and environmental conditions appear conducive for gradual development.

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Oct. 16, 2023 -- Cerebras Systems, a pioneer in accelerating generative AI ... This will allow users to build and train the next wave of cutting-edge foundational models, while greatly reducing training times and accelerating time-to-insight.”

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Oct. 16, 2023 — Cerebras Systems, a pioneer in accelerating generative AI ... This will allow users to build and train the next wave of cutting-edge foundational models, while greatly reducing training times and accelerating time-to-insight.”

Authors:
(1) Omer Rathore, Department of Physics, Durham University;
(2) Alastair Basden, Department of Physics, Durham University;
(3) Nicholas Chancellor, Department of Physics, Durham University and School of Computing, Newcastle University;
(4) Halim Kusumaatmaja, Department of Physics, Durham University and Institute for Multiscale Thermofluids, School of Engineering, The University of Edinburgh. Table of Links Abstract and Introduction Methods Quantum Annealing
Adaptive Mesh Refinement
Smoothed Particle Hydrodynamics Results Grid Based Application
Particle Based Application Conclusions and Outlook, Acknowledgements, and References Quantum Annealing Of the myriad possibilities[42] when it comes to implementing a quantum computer, currently the two leading paradigms are gate based quantum computing (QC)[43, 44] and adiabatic quantum computing (AQC)[45, 46]. In principle the two approaches have been shown[47] to be equivalent if allowing a polynomial overhead. Gate based QC can be thought of as the quantum analogue to classical computing where instead of logical gates acting on bits, the computation is performed by applying unitary gates to qubits. Alternatively, AQC relies on adiabatic time evolution of a quantum state from an initial, easy to prepare state to a final observed value as modelled by the Schrödinger equation. Moreover by operating under the umbrella of the adiabatic theorem, the protocol is guaranteed to obtain the ground state solution, at least in theory. However, in practice the requirements of true adiabacity and changing the Hamiltonian slowly enough can be excessively stringent. This is clearly evident in current architecture where thermal coupling with the environment is strong enough such that the timescales are of the order ∼ 10−100ns[53]. Furthermore the requirements on how quickly the Hamiltonian can be evolved (i.e. the annealing schedule) is dependant on the gap between the ground state and first excited solution, which is not usually known a priori. QA is thus a relaxation of these conditions that follows the same principles as AQC, but forms a distinctly separate algorithm, with the annealing schedule determined heuristically and strictly adiabatic conditions not guaranteed. The same time dependant Hamiltonian of Equation 1 is used to evolve the quantum state, however the system can no longer accurately be modeled by the Schrödinger equation, but would require master-equation based descriptions. As a result, QA forms a heuristic quantum algorithm that should be viewed as a statistical sampler rather than a deterministic solver, with the intended goal of maintaining a relatively high probability of remaining in the ground state or to at least be sufficiently close. The theory of quantum annealing is much less developed than AQC, partially due to the more complex setting. However, some progress has been made, for example in the topic of diabatic computing which considers rapid quenches far from the adiabatic limit[54]. In particular, in this regime a mechanism related to energy conservation provides an important guarantee on average optimality[55]. The expectation that Quantum Annealing (QA) might surpass classical algorithms is tied to the potential impact of quantum mechanical phenomena such as superposition, tunneling, and entanglement[31], [45] [57–59]. Fundamentally, quantum superposition and tunneling can enable transitions between states, even those separated by high energy barriers[60]. This suggests that a search algorithm utilizing QA could overcome local minima more easily by tunneling through these energy barriers as illustrated in Figure 1. QA is thus grounded in a model that more closely reflects the behavior of real quantum systems when compared to AQC. However, the potential for non-adiabatic effects complicates the distinction between its computational complexity and that of conventional computing. QA often involves the non-adiabatic evolution of mixed quantum states within an open system, and this approach is generally considered heuristic. Thus, it lacks the provable computational advantages that AQC provides[61]. The general approach to employing a quantum annealer shares many similarities across different architectures. This research, however, utilises D-Wave systems, which consist of superconducting qubits. Although there are several promising alternatives[62–64], these technologies are comparatively nascent in their development. Meanwhile D-Wave is the largest and most commonly used commercial QA platform currently and has been used extensively for both industry and research purposes. For a detailed, step-by-step guide on using a quantum annealer, interested readers are encouraged to consult the numerous introductory articles available on this topic[31], [61], [65]. In summary, the primary steps involved in utilizing an annealer include problem formulation, minor embedding, and sampling (i.e. the anneal itself). Problem formulation and how the classical simulations were run is described next, with the influence of embedding and sampling discussed as part of the results. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Omer Rathore, Department of Physics, Durham University; (2) Alastair Basden, Department of Physics, Durham University; (3) Nicholas Chancellor, Department of Physics, Durham University and School of Computing, Newcastle University; (4) Halim Kusumaatmaja, Department of Physics, Durham University and Institute for Multiscale Thermofluids, School of Engineering, The University of Edinburgh. Authors: Authors: (1) Omer Rathore, Department of Physics, Durham University; (2) Alastair Basden, Department of Physics, Durham University; (3) Nicholas Chancellor, Department of Physics, Durham University and School of Computing, Newcastle University; (4) Halim Kusumaatmaja, Department of Physics, Durham University and Institute for Multiscale Thermofluids, School of Engineering, The University of Edinburgh. Table of Links Abstract and Introduction Abstract and Introduction Abstract and Introduction Methods Methods Quantum Annealing Adaptive Mesh Refinement Smoothed Particle Hydrodynamics Quantum Annealing Quantum Annealing Adaptive Mesh Refinement Adaptive Mesh Refinement Smoothed Particle Hydrodynamics Smoothed Particle Hydrodynamics Results Results Grid Based Application Particle Based Application Grid Based Application Grid Based Application Particle Based Application Particle Based Application Conclusions and Outlook, Acknowledgements, and References Conclusions and Outlook, Acknowledgements, and References Conclusions and Outlook, Acknowledgements, and References Quantum Annealing Of the myriad possibilities[42] when it comes to implementing a quantum computer, currently the two leading paradigms are gate based quantum computing (QC)[43, 44] and adiabatic quantum computing (AQC)[45, 46]. In principle the two approaches have been shown[47] to be equivalent if allowing a polynomial overhead. Gate based QC can be thought of as the quantum analogue to classical computing where instead of logical gates acting on bits, the computation is performed by applying unitary gates to qubits. Alternatively, AQC relies on adiabatic time evolution of a quantum state from an initial, easy to prepare state to a final observed value as modelled by the Schrödinger equation. Moreover by operating under the umbrella of the adiabatic theorem, the protocol is guaranteed to obtain the ground state solution, at least in theory. However, in practice the requirements of true adiabacity and changing the Hamiltonian slowly enough can be excessively stringent. This is clearly evident in current architecture where thermal coupling with the environment is strong enough such that the timescales are of the order ∼ 10−100ns[53]. Furthermore the requirements on how quickly the Hamiltonian can be evolved (i.e. the annealing schedule) is dependant on the gap between the ground state and first excited solution, which is not usually known a priori. QA is thus a relaxation of these conditions that follows the same principles as AQC, but forms a distinctly separate algorithm, with the annealing schedule determined heuristically and strictly adiabatic conditions not guaranteed. The same time dependant Hamiltonian of Equation 1 is used to evolve the quantum state, however the system can no longer accurately be modeled by the Schrödinger equation, but would require master-equation based descriptions. As a result, QA forms a heuristic quantum algorithm that should be viewed as a statistical sampler rather than a deterministic solver, with the intended goal of maintaining a relatively high probability of remaining in the ground state or to at least be sufficiently close. The theory of quantum annealing is much less developed than AQC, partially due to the more complex setting. However, some progress has been made, for example in the topic of diabatic computing which considers rapid quenches far from the adiabatic limit[54]. In particular, in this regime a mechanism related to energy conservation provides an important guarantee on average optimality[55]. The expectation that Quantum Annealing (QA) might surpass classical algorithms is tied to the potential impact of quantum mechanical phenomena such as superposition, tunneling, and entanglement[31], [45] [57–59]. Fundamentally, quantum superposition and tunneling can enable transitions between states, even those separated by high energy barriers[60]. This suggests that a search algorithm utilizing QA could overcome local minima more easily by tunneling through these energy barriers as illustrated in Figure 1. QA is thus grounded in a model that more closely reflects the behavior of real quantum systems when compared to AQC. However, the potential for non-adiabatic effects complicates the distinction between its computational complexity and that of conventional computing. QA often involves the non-adiabatic evolution of mixed quantum states within an open system, and this approach is generally considered heuristic. Thus, it lacks the provable computational advantages that AQC provides[61]. The general approach to employing a quantum annealer shares many similarities across different architectures. This research, however, utilises D-Wave systems, which consist of superconducting qubits. Although there are several promising alternatives[62–64], these technologies are comparatively nascent in their development. Meanwhile D-Wave is the largest and most commonly used commercial QA platform currently and has been used extensively for both industry and research purposes. For a detailed, step-by-step guide on using a quantum annealer, interested readers are encouraged to consult the numerous introductory articles available on this topic[31], [61], [65]. In summary, the primary steps involved in utilizing an annealer include problem formulation, minor embedding, and sampling (i.e. the anneal itself). Problem formulation and how the classical simulations were run is described next, with the influence of embedding and sampling discussed as part of the results. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Load Balancing For High Performance Computing
Using Quantum Annealing: Quantum Annealing

Do you think AI is big? Well, quantum computing will be much bigger. Quantum computing is expected to have a significant impact on several key industries like Finance, Healthcare, Cybersecurity, Logistics, AI and ML, Chemistry, Defense, Aerospace, Energy, Telecommunications, the list goes on and on. Briefly: Quantum computing uses quantum mechanics to do complex calculations that regular computers can't handle. With quantum bits (qubits) that can be in multiple states at once, these computers could change fields like cryptography, healthcare, and finance. I looked into the current state of the industry, starting with trends and diving deeper. I did research to understand what the industry looks like today. I started by looking at the trend, then wanted to find something more interesting and went down the rabbit hole. I found lots of data that could be useful for investors, entrepreneurs, and engineers who are thinking about starting something new. Here, in this report, we have industry leaders, startups, recent investments, grants, and some business ideas. Let’s Start With Some Nerdy Stats Quantum computers need to be super cold, almost at absolute zero (-273°C or -460°F). Funding for quantum tech startups jumped from $700 million in 2020 to $1.4 billion in 2021. It's predicted to hit $64.98 billion by 2030, growing 56.0% annually from 2021 to 2030. China plans to invest roughly $15 billion in quantum tech, the most worldwide. IBM aims to have a 1,000-qubit quantum computer by 2023. Google achieved quantum supremacy in 2019 using a 53-qubit processor. Quantum computers could solve problems in seconds that classical computers would take billions of years to crack. Physicist Richard Feynman first suggested quantum computing in 1982, but practical quantum computers are still in their early stages almost 40 years later. Big Tech Is Crushing It (as Always). IBM: Developed Qiskit framework and offers cloud-based quantum systems.Google- Achieved quantum supremacy in 2019 and created Cirq library.Microsoft- Developing Azure Quantum platform and Q# language.Amazon- Offers Braket, a fully managed quantum computing service.D-Wave Systems- Develops quantum annealing processors and Ocean software suite. Popular Quantum Tools Qiskit: Open-source quantum computing framework for building quantum programs. Cirq: Python library for writing, manipulating, and optimizing quantum circuits. Q#: Microsoft's open-source programming language for quantum computing. Ocean: D-Wave's suite of tools for solving optimization problems on quantum computers. Strawberry Fields: Xanadu's cross-platform Python library for simulating and executing quantum algorithms. Startups and Recent Investments: I wanted to find small players too, but it’s rare that someone will start a quantum computing business without significant funding. Here are some startups that making the noise. Quantum Source, Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources.


Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science.


Quantum Machines, Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers.


Classiq, Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits.


Multiverse Computing, Spanish quantum software company founded in 2019 Nanofiber Quantum Technologies (NanoQT) Raised $8.5 million from Phoenix Venture Partners (US), JAFCO Group, SPARX Group, Keio Innovation Initiative, and Waseda University Ventures (Japan). QphoX Received €8.0M (~$8.7M) led by QDNL Participations, alongside the EIC Fund, Quantonation, Speedinvest, High-Tech Gründerfonds, and Delft Enterprises. Rebellions Raised $124.0M in Series B funding led by KT Corp with participation from several Korean investors. Quantum Business Ideas and How to Jump In It seems challenging for small players or startups to enter the quantum computing industry with limited investments due to several factors: High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities.


Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies.


Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding.


Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue But Still, There’s a Chance Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals.


Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape.


Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts.


Create quantum computing education and training programs for developers and researchers.


Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups.


Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Try to Apply for Grants I made a list of active grants for doing research in quantum computing across the US, Europe, the Middle East, and Asia. Some of these grants are: NSF Quantum Leap Challenge Institutes
European Innovation Council (EIC) funding
Technology Innovation Institute (TII) in Abu Dhabi
Singapore Quantum Engineering Programme (QEP)
UNICEF Innovation Fund More research data, with more startups, funding, and grants can be found in the report (it’s free) I hope you enjoyed it and found something useful for you. If this entangled your curiosity a little bit, feel free to share it with your friends and colleagues. Do you think AI is big? Well, quantum computing will be much bigger. Quantum computing is expected to have a significant impact on several key industries like Finance, Healthcare, Cybersecurity, Logistics, AI and ML, Chemistry, Defense, Aerospace, Energy, Telecommunications, the list goes on and on. Briefly : Briefly Quantum computing uses quantum mechanics to do complex calculations that regular computers can't handle. With quantum bits (qubits) that can be in multiple states at once, these computers could change fields like cryptography, healthcare, and finance. I looked into the current state of the industry, starting with trends and diving deeper. I did research to understand what the industry looks like today. I started by looking at the trend, then wanted to find something more interesting and went down the rabbit hole. I found lots of data that could be useful for investors, entrepreneurs, and engineers who are thinking about starting something new. Here, in this report, we have industry leaders, startups, recent investments, grants, and some business ideas. research Let’s Start With Some Nerdy Stats Quantum computers need to be super cold, almost at absolute zero (-273°C or -460°F). Quantum computers need to be super cold, almost at absolute zero (-273°C or -460°F). zero Funding for quantum tech startups jumped from $700 million in 2020 to $1.4 billion in 2021. It's predicted to hit $64.98 billion by 2030, growing 56.0% annually from 2021 to 2030. Funding for quantum tech startups jumped from $700 million in 2020 to $1.4 billion in 2021. It's predicted to hit $64.98 billion by 2030, growing 56.0% annually from 2021 to 2030 . 2030 China plans to invest roughly $15 billion in quantum tech, the most worldwide. China plans to invest roughly $15 billion in quantum tech, the most worldwide . worldwide IBM aims to have a 1,000-qubit quantum computer by 2023. IBM aims to have a 1,000-qubit quantum computer by 2023 . 2023 Google achieved quantum supremacy in 2019 using a 53-qubit processor. Google achieved quantum supremacy in 2019 using a 53-qubit processor . processor Quantum computers could solve problems in seconds that classical computers would take billions of years to crack. Quantum computers could solve problems in seconds that classical computers would take billions of years to crack . crack Physicist Richard Feynman first suggested quantum computing in 1982, but practical quantum computers are still in their early stages almost 40 years later. Physicist Richard Feynman first suggested quantum computing in 1982, but practical quantum computers are still in their early stages almost 40 years later . later Big Tech Is Crushing It (as Always). IBM : Developed Qiskit framework and offers cloud-based quantum systems. Google - Achieved quantum supremacy in 2019 and created Cirq library. Microsoft - Developing Azure Quantum platform and Q# language. Amazon - Offers Braket, a fully managed quantum computing service. D-Wave Systems - Develops quantum annealing processors and Ocean software suite. IBM Google Microsoft Amazon D-Wave Systems Popular Quantum Tools Qiskit : Open-source quantum computing framework for building quantum programs. Qiskit Cirq : Python library for writing, manipulating, and optimizing quantum circuits. Cirq Q# : Microsoft's open-source programming language for quantum computing. Q# Ocean : D-Wave's suite of tools for solving optimization problems on quantum computers. Ocean Strawberry Fields : Xanadu's cross-platform Python library for simulating and executing quantum algorithms. Strawberry Fields Startups and Recent Investments: I wanted to find small players too, but it’s rare that someone will start a quantum computing business without significant funding. Here are some startups that making the noise. Quantum Source, Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources. Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science. Quantum Machines, Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers. Classiq, Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits. Multiverse Computing, Spanish quantum software company founded in 2019 Quantum Source, Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources. Quantum Source , Founded in 2021, based in Israel. Developing quantum random number generators and entropy sources. Quantum Source Quantum Source Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science. Quantum Art - Founded in 2022, based in Israel. Develops ion trap quantum computers based on research from the Weizmann Institute of Science. Quantum Art Quantum Art Quantum Machines, Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers. Quantum Machines , Founded in 2018, based in Israel. Develops quantum control systems for superconducting quantum computers. Quantum Machines Quantum Machines Classiq, Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits. Classiq , Founded in 2020, based in Israel. Provides software to model, synthesize, and analyze quantum circuits. Classiq Classiq Multiverse Computing, Spanish quantum software company founded in 2019 Multiverse Computing, Spanish quantum software company founded in 2019 Multiverse Computing, Multiverse Computing, Nanofiber Quantum Technologies (NanoQT) Raised $8.5 million from Phoenix Venture Partners (US), JAFCO Group, SPARX Group, Keio Innovation Initiative, and Waseda University Ventures (Japan). Nanofiber Quantum Technologies (NanoQT) Raised $8.5 million from Phoenix Venture Partners (US), JAFCO Group, SPARX Group, Keio Innovation Initiative, and Waseda University Ventures (Japan). Nanofiber Nanofiber QphoX Received €8.0M (~$8.7M) led by QDNL Participations, alongside the EIC Fund, Quantonation, Speedinvest, High-Tech Gründerfonds, and Delft Enterprises. QphoX Received €8.0M (~$8.7M) led by QDNL Participations, alongside the EIC Fund, Quantonation, Speedinvest, High-Tech Gründerfonds, and Delft Enterprises. QphoX QphoX Rebellions Raised $124.0M in Series B funding led by KT Corp with participation from several Korean investors. Rebellions Raised $124.0M in Series B funding led by KT Corp with participation from several Korean investors. Rebellions Rebellions Quantum Business Ideas and How to Jump In It seems challenging for small players or startups to enter the quantum computing industry with limited investments due to several factors: High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities. Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies. Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding. Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities. High infrastructure costs: Building quantum computers requires specialized hardware like cryogenic cooling systems, precision control electronics, and high-end fabrication facilities. Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies. Talent shortage: There is a significant lack of workforce with the interdisciplinary skills (quantum physics, mathematics, computer science, engineering) needed to develop quantum technologies. Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding. Long-time horizons: Startups need to sustain long periods of R&D without near-term revenue, which requires substantial funding. Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue Current market demand for quantum computing and commercial applications is still limited and speculative. This makes it risky for startups relying on near-term revenue But Still, There’s a Chance Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals. Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape. Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts. Create quantum computing education and training programs for developers and researchers. Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups. Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals. Learn fast. Apply for courses and programs, read a lot, and visit events to network with professionals. Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape. Start a news platform with curated news, analysis, and insights on the rapidly evolving quantum computing landscape. Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts. Build an online community for collaboration, knowledge sharing, and networking among quantum researchers, developers, and enthusiasts. Create quantum computing education and training programs for developers and researchers. Create quantum computing education and training programs for developers and researchers. Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups. Offer marketing, content creation (blogs, videos, infographics), and social media management services tailored to quantum technology companies and startups. Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Start a niche recruitment firm that specializes in sourcing and matching quantum talent (physicists, engineers, programmers). Try to Apply for Grants Try to Apply for Grants I made a list of active grants for doing research in quantum computing across the US, Europe, the Middle East, and Asia. Some of these grants are: NSF Quantum Leap Challenge Institutes European Innovation Council (EIC) funding Technology Innovation Institute (TII) in Abu Dhabi Singapore Quantum Engineering Programme (QEP) UNICEF Innovation Fund NSF Quantum Leap Challenge Institutes NSF Quantum Leap Challenge Institutes NSF Quantum Leap Challenge Institutes European Innovation Council (EIC) funding European Innovation Council (EIC) funding European Innovation Council (EIC) funding Technology Innovation Institute (TII) in Abu Dhabi Technology Innovation Institute (TII) in Abu Dhabi Technology Innovation Institute (TII) in Abu Dhabi Singapore Quantum Engineering Programme (QEP) Singapore Quantum Engineering Programme (QEP) Singapore Quantum Engineering Programme (QEP) UNICEF Innovation Fund UNICEF Innovation Fund UNICEF Innovation Fund More research data, with more startups, funding, and grants can be found in the report (it’s free) the report report I hope you enjoyed it and found something useful for you. If this entangled your curiosity a little bit, feel free to share it with your friends and colleagues.

The Analysis of The Future of Quantum Computing

While the quantum technology scene may be just booting up, there is one place that seems to be making quantum leaps in the space, metaphorically speaking, and that place is not Silicon Valley. It’s Ontario, Canada. Even amidst a general consensus that “prototype quantum computing hardware is still embryonic” ( August 2018), there is a growing set of Canadian technologists between Toronto and Waterloo already off to the races in hopes of using their first mover advantage to develop, commercialize and cash-in on a qubit-driven future. Wired Canada‘s “quantum valley” is poised to win — they have a 16 year advantage in building and commercializing the technology, private and government support, an influx of scientific talent, and an exploding startup scene. I’m watching it firsthand, having moved from NYC to Toronto recently, and I’ll share more on why I’m bullish in a minute. But first, let’s quickly unpack how quantum computing works and why it’s going to be a game-changer. How does quantum computing work exactly? I refer to this quick explainer from : Motherboard “Present day computers are limited by their hardware. They use electrical circuits that are switched on or off, in a 0 or 1 position. Quantum computing would change that by using particles called qubits, which are suspended in a super-cold environment where the temperature nears absolute zero. The network formed by these particles allows for processing power to grow exponentially, as the qubits can be simultaneously at a 0 and a 1.” Many tasks that supercomputers find challenging today —chemistry simulations, code-breaking, creating general artificial intelligence — are incredibly simple for the quantum computer. Microsoft CEO Satya Nadella is a believer. At a conference in 2017, he implored developers to begin working on quantum problems (using Microsoft’s open source tools) as the technology would “help us tackle some of the biggest challenges we face” ( ) by enabling massive breakthroughs in medicine, energy and finance. Wired In addition to Microsoft, other giants including Google, IBM and Intel are focusing heavily on developing quantum technology, and alongside them, fast-growing startups like Xanadu and Rigetti Computing. “In 2017, venture investors plowed $241 million into working on quantum computing hardware or software worldwide, according to CB Insights. That’s triple the amount in the previous year.” ( ) startups Wired By 2024, the estimated will reach $10.7 billion, which explains why nations, corporates and startups alike are all jockeying for first position. global market for quantum technologies What’s the deal in Canada? There’s something in the water here in Ontario that leads me to believe they will crack the quantum code first. Here’s why: 1. They “fired the starting gun” These are the words of Raymond LaFlamme, Canadian physicist and previous director of the Institute for Quantum Computing (IQC) at the University of Waterloo. According to LaFlamme, the launch of the IQC sixteen years ago in 2002 “fired the starting gun in this race”, years before the United States, China and the United Kingdom started dedicating significant resources to quantum research. The IQC was born out of a massive personal donation from Mike Lazaridis, founder of BlackBerry, who saw quantum as his opportunity to be central to the next technological revolution. Since 2002, Lazaridis has invested more than $100 million into the IQC to conduct cross-disciplinary research and create an ecosystem ready to support early-stage, high-risk/high-reward opportunities in the space. If you’re looking for some social proof, LaFlamme’s previous supervisor, the late Stephen Hawking, was impressed: Raymond LaFlamme (left) with Stephen Hawking. Photo Courtesy of the Institute for Quantum Computing 2. They were the first to commercialize British Columbia is home to , the first company to have commercialized a quantum computing hardware system. D-Wave was founded in 1999, three years before the IQC, and although it’s based on the Canadian west coast, D-Wave’s early entrance and success has rippled across the country and acted as a catalyst for continued conversation across investors, technologists and corporates. D-Wave Systems Christian Weedbrook, CEO of Toronto-based quantum photonics company , told me “everyone knows about D-Wave. How are you different from D-Wave? You get that question a lot [from investors] which is an opportunity to talk more about what we’re doing.” Xanadu With over $200 million raised, the highest share of patents across all companies in the space, and a customer roster that includes Google, NASA, Lockheed Martin and “an unnamed U.S. intelligence agency”, D-Wave is a formidable force working in Canada’s favor. Source: Relecura Quantum Computing: IP Report 2018 3. They boast both private and government support In addition to the private investments from Mike Lazaridis and his VC firm Quantum Valley Investments, the Ontario and Canadian governments have both invested heavily — to the tune of $1 billion in the last decade alone — alongside Lazaridis and others to build the infrastructure and resources needed for quantum dominance. This private-public partnership is responsible for the creation of the , the , the and the Quantum Valley Ideas Lab, all based in Waterloo and focused on different elements of the quantum research life-cycle — from R&D all the way through new product commercialization. Institute for Quantum Computing Perimeter Institute for Theoretical Physics Quantum NanoFab Facility 4. They’re encouraging an influx of technical talent Beyond financing research and infrastructure, the Canadian government is also supporting a flood of scientific talent through favorable economic and immigration policies. According to Forbes, 43% of Fortune 500 companies were founded by immigrants or their children, and the top quantum companies will be no different. Recognizing this, the Canadian government has created tangible programs to incentivize the immigration of foreign entrepreneurs and scientists: First, the offers an alternative, fast-track for highly skilled foreign workers to immigrate as permanent residents by demonstrating “unique and/or specialized talent” and bypassing the typical immigration requirements. Through this program, Canadian employers can recruit top talent and secure work permits in as quickly as 10 business days. Global Skills Strategy Second, Canada’s program is perhaps the most globally progressive, with $4.6 million in funding slated for 2018. Similar to the Global Skills Strategy, it encourages foreign workers, but is primarily aimed at making it easier for startup CEOs to enter the country, secure venture funding and create jobs for Canadians. Startup Visa In contrast, the US has become less attractive for international talent because of increasingly restricted immigration policies under the Trump administration, which will no doubt hinder its long-term quantum aspirations. 5. The startup scene is primed for growth As a result of the confluence of world-class research institutions, healthy investments, government support and talent, the Ontario startup community is like a revved engine. In fact, many of the brightest minds are now working together at the world’s first quantum-focused tech accelerator, a sub-program of the (CDL) in Toronto. Creative Destruction Lab The CDL is betting that this density will play a role in tipping the scales in Canada’s favor. The accelerator, which accepted 21 companies and 40 quantum physicists into 2017's inagural program, that “by 2022 it will have created more commercially viable, well-capitalized, revenue-generating quantum machine learning companies than the rest of the world combined”. predicts Xanadu, one of the rising stars from CDL (who participated in the program a year before the quantum track was officially unveiled), agrees. According to CEO Christian Weedbrook, these incubator programs “are attracting a lot of talent” which is critical to solving the tough technological challenges posed by quantum. Xanadu itself is an example of what’s possible, as they are competing on a global scale already, recently winning major pilots away from the large corporates. Why does it matter? While it’s not yet clear what the first killer quantum application will be, it is clear that the nation that creates it first will gain enormous economic, political and national security advantages. Whether it’s used to decrypt and expose secrets, to patent medical breakthroughs, or render computer systems hack-proof, one thing is for certain — quantum technology has the power to dramatically alter the course of history in the direction of it’s conqueror. With stakes that high, the global race is on. At this early stage, it is definitely still anyone’s game, but with the wind at their backs and a healthy head start, the quantum race is Canada’s to lose. Please note: views my own and may not reflect not those of my employer

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