Zug, Switzerland, 20th November, 2022, Chainwire Powered by the Tezos blockchain, 3Route enables cost-efficient and secure swap...

U.S. Senator Cynthia Lummis believes that the FTX bankruptcy wouldn’t have happened under the Lummis-Gillibrand crypto bill. She stressed: “It’s clearer now than...

Buy and sell Bitcoin the easy way Start your crypto portfolio today! ...

Physicists in Israel have printed a micro-optical element that generates a twisted Bessel beam on...

Crypto may have been "founded on the idea of decentralization," says Gensler, but that hasn't stopped centralization from emerging in the market.

In one of the biggest and most unexpected developments of the season, Call of Duty veteran, Clayster, has been benched by NYSL. It was a move that some may have seen coming, but it still came as quite a shock to all involved. There was a debacle surrounding the announcement, as essentially, the League leaked […]

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Quantum 6, 667 (2022).

https://doi.org/10.22331/q-2022-03-11-667

Quantum error correcting codes (QECCs) are the means of choice whenever quantum systems suffer errors, e.g., due to imperfect devices, environments, or faulty channels. By now, a plethora of families of codes is known, but there is no universal approach to finding new or optimal codes for a certain task and subject to specific experimental constraints. In particular, once found, a QECC is typically used in very diverse contexts, while its resilience against errors is captured in a single figure of merit, the distance of the code. This does not necessarily give rise to the most efficient protection possible given a certain known error or a particular application for which the code is employed. In this paper, we investigate the loss channel, which plays a key role in quantum communication, and in particular in quantum key distribution over long distances. We develop a numerical set of tools that allows to optimize an encoding specifically for recovering lost particles both deterministically and probabilistically, where some knowledge about $what$ was lost is available, and demonstrate its capabilities. This allows us to arrive at new codes ideal for the distribution of entangled states in this particular setting, and also to investigate if encoding in qudits or allowing for non-deterministic correction proves advantageous compared to known QECCs. While we here focus on the case of losses, our methodology is applicable whenever the errors in a system can be characterized by a known linear map.

 Investing in volatile assets such as cryptocurrencies can be tricky since it requires traders to gauge the market 24/7. However, tools like the stock-to-flow (S2F) model can be used to make investments rationally. Just like the traditional capital asset pricing model (CAPM), the S2F model can help anticipate the price of a cryptocurrency like Bitcoin. Let’s understand what is the stock-to-flow (S2F) model and analyze its accuracy for crypto price prediction in this article. Stock-to-flow ratio Explained The S2F ratio provides a number that indicates the number of years crypto will take to reach the current supply (at the current production rate). In general, with the highest number, the crypto asset will be more expensive too. An institutional investor called “Plan B” popularized the concept of the S2F ratio. The SF ratio has a long history of being connected with the price of Bitcoin (BTC), making it a popular approach for predicting future BTC price estimates. Bitcoin is the first and most well-known rare digital object globally, and its supply is limited, just like silver and gold, with only 21 million coins in circulation. The value of Bitcoin increases because of its scarcity, and the S2F takes advantage of this fact to predict Bitcoin’s future price. Bitcoin’s core technology ensures that the number of new coins issued decreases over time, increasing scarcity.  The miner who calculates the hash required to validate a block of transactions, creating a proof-of-work, receives a “block reward,” which is halved after every 210,000 blocks called Bitcoin Halving. The block reward has decreased from 50 BTC in 2009 to 6.25 BTC in 2020. In 2012, it was 25 BTC and 12.5 BTC in 2016, and in the spring of 2024, the next halving will occur. Due to this halving event, BTC’s price rises. The justification can be found in economics- when supply is reduced, scarcity increases, and price hikes too. The scarcity can further be used to forecast future prices or the best time to invest in BTC. The significant amount of scarcity can be evidenced by a higher ratio. Cryptocurrency is similar to precious metals like gold and silver since it cannot be converted into components and is rare. The value generated by the S2F is a relative value that makes it easy to calculate the ratio. The stock-to-flow ratio compares a commodity’s current stock (the total amount available) to new production flow (amount mined during a specific year). Therefore, S2F= Stock/Flow. Let’s understand how to compute the S2F ratio: The stock of Bitcoin was 18,847,331 BTC in October 2021, which is 89.74% of the total supply. The number that represents the stock is subject to change as new blocks are mined every 10 minutes. The flow of BTC at the same time was 328,500. When these numbers are imputed into the stock/flow formula (18,847,331/328,500), the result is an S2F ratio of 57.374. As a result, mining the entire BTC supply would take about 57 years without considering the maximum supply and halving events. Additionally, Bitcoin halving events raise the S2F ratio by increasing scarcity, which causes the price of Bitcoin to rise. For investors to understand why Bitcoin is categorized as a currency rather than a commodity, this is the most significant statistic. Limitations of the stock-to-flow ratio The model ignores the demand of a cryptocurrency while computing the ratio and considering only supply. However, both demand and supply factors are equally essential to determining asset price. Hence, if demand falls for BTC, the price will decline too; it doesn’t matter if the halving event leads to BTC price rise. Volatile price swings influence the cryptocurrency market, and in periods of high volatility, an investor may sell their holdings. This reaction may lead to the price decline due to the liquidation of the long positions. The S2F ratio ignores the volatility factor too. Another hypothetical situation like a black swan event may prohibit investors from trading cryptocurrencies, leading to a decline in the price of digital assets under consideration. The S2F ratio does not take this factor into account while predicting the future price of BTC. How to trade using the stock-to-flow ratio? Learning how to use the stock-to-flow approach in cryptocurrency trading could be advantageous despite these shortcomings. According to the model’s history, when a cryptocurrency’s stock-to-flow ratio rises, so does its value. This connection can assist you in making investment decisions. A high stock-to-flow ratio, such as 60 or above, indicates that relative scarcity is high, meaning that prices will rise as well. However, when investors see this ratio, they may decide to sell some of their Bitcoin to profit from the current high price. They may also buy more if the ratio is low but predicted to rise in the future. Understanding how to leverage the stock-to-flow ratio in crypto can … Continued

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Practical Ways to Improve Your Sleep as an Esports Athlete Introduction In my last blog we discussed three reasons why sleep is important for your esports performance. If you haven’t read that yet I’d definitely recommend giving it a read at some point to help you understand why sleep is important. (Click here) In this […]